European J. of Industrial Engineering (38 papers in press)

Regular Issues

• Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply  
  by Guodong Yu, Pengcheng Dong, Ying Xu, Xiao Zhao 
  Abstract: This paper considers a joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty. Under the uncoordinated inventory policy, we propose a chance-constrained risk-averse bi-objective 01 mixed-integer nonlinear stochastic programming to minimise the total expected cost and CO2 emissions. To solve the model, we first present an equivalent reformulation with a single objective based on distributionally robust optimisation. Then, we provide a linear reformulation with some valid inequalities. We also provide a greedy heuristic decomposition searching rule to solve the large-scale problem. We finally present a numerical analysis to show the performance of our methods. Results illustrate that the risk-averse joint model can effectively improve service capability and reliability than independent and risk-neutral location and inventory problems. We also recommend that the incompletely uncoordinated strategy for the joint optimisation can be more cost-effective and generate fewer workloads. Besides, the proposed algorithm achieves a more desirable performance than CPLEX for large-scale problems.
  Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
  DOI: 10.1504/EJIE.2023.10046132
   
  
• A survey on network design problems: main variants and resolution approaches  
  by Imen Mejri, Safa Bhar Layeb, Farah Zeghal 
  Abstract: Over the last decades, network design problems (NDPs) have been one of the most investigated combinatorial optimisation problems that are still catching the interest of both practitioners and researchers. In fact, NDPs pose significant algorithmic challenges, as they are notoriously NP-hard, and arise in several applications, mainly in logistics, telecommunication, and production systems. Based on the literature published mainly between 1962 and 2021, this paper provides a comprehensive taxonomy of NDPs and also identifies the most investigated variants as well as their main fields of application. This taxonomy highlights the diversity as well as the assets of this core class of operations research problems. Moreover, the main mathematical formulations and solution methods are reported. Finally, directions for future research on NDPs are derived.
  Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation.
  DOI: 10.1504/EJIE.2022.10046171
   
  
• An EPQ model with different demand and deterioration rate for two warehouses under shortage, learning and imperfect production.  
  by S. V. Singh Padiyar, Vandana Gupta, S.R. Singh, Naveen Bhagat 
  Abstract: This paper presents a mathematical framework to obtain a production model for deteriorating items with learning effect in production cost. The study considers different demand rates and different deterioration rate. In this model, one is own warehouse (OW) and other one is rented warehouse (RW) with different demand rate is considered. Every producer wants to get maximum benefit in his business, and he want to vacate the RW very soon, due to which he has to pay the least rent, so demand rate for RW is strictly increasing function of time. On the contrary, he can use his OW in such a way that the producer gets benefit and can build the selling price of inventory according to his profit, so demand rate for OW is selling price dependent. These assumptions effects on demand therefore production rate is taken as demand dependent. Shortage is also considered. Numerical example and sensitivity analysis of some parameters provided to examine the impact on the optimal total cost of the system. [Submitted: 28 January 2022; Accepted: 23 August 2023]
  Keywords: two warehouses; imperfect production; shortage; deterioration; learning effect.
  DOI: 10.1504/EJIE.2025.10060653
   
  
• A hybrid approach of genetic algorithm and truncated branch-and-bound for seru scheduling problem with sequence-dependent setup time  
  by Xiaohong Zhang, Zhe Zhang, Xiaoling Song, Xiaofang Zhong 
  Abstract: This paper concentrates on the seru scheduling problem considering sequence-dependent setup time to minimise the makespan, in which seru production system (SPS) is a new-type advanced manufacturing system to respond quickly to volatile market. A mixed-integer programming (MIP) model is formulated, and then a hybridisation of genetic algorithm with a truncated branch-and-bound method (GATBB) is designed to speed up the solving process. Truncated branch-and-bound (TBB) procedure is employed to find a better solution than the initial one given by the GA within a tighter upper bound. Computational experiments are carried out finally, and a series of results of experiments, analyses of variance (ANOVA), and Tukey test show that the GATBB algorithm significantly outperforms the GA and GA-PSO algorithm. Specifically, GATBB algorithm performs extremely well in finding high-quality solutions efficiently, and can find approximate and even exact solutions for instances with up to 100 products. [Submitted: 31 October 2022; Accepted: 25 September 2023]
  Keywords: seru production system; setup times; scheduling; genetic algorithm; branch-and-bound.
  DOI: 10.1504/EJIE.2025.10060760
   
  
• Applying a Modified Adaptive Large Neighborhood Search for Truck Scheduling and Pile Assignment in a Two-Stage Sorting System  
  by James C. Chen, Tzu-Li Chen, Yin-Yann Chen, Yung-Hsin Su 
  Abstract: In this study, we tackle the complexities of a two-stage semi-automatic sorting system, considering the diverse distribution requirements of parcels and the constraints imposed by sorting equipment. Our objective is to integrate two decision points the inbound truck schedule and the parcel sorting plan to minimise overall operational costs. We first formulate the problem using a mixed-integer linear programming model and then propose a mixed-coded modified adaptive large neighbourhood search (MCMALNS) algorithm to enhance performance. In our computational study, the proposed approach demonstrated the ability to quickly obtain high-quality solutions compared to other algorithms. Furthermore, a full factorial experiment was conducted to analyse cost variations across 36 scenarios. Factors including loading, deadline, arrival pattern, pile/commodity ratio, and algorithm were all identified as significant and exhibited considerable influence on the outcomes. The insights derived from this analysis provide valuable guidance for management personnel in decision-making. [Submitted: 30 January 2023; Accepted: 25 August 2023]
  Keywords: truck scheduling; two-stage sorting system; modified adaptive large neighbourhood search.
  DOI: 10.1504/EJIE.2025.10061219
   
  
• Pricing and Greening Strategies in a Dual-channel Supply Chain with Government tariffs and Cannibalisation under Demand Uncertainty  
  by Amit Ranjan, Anand Ranjan, J.K. Jha 
  Abstract: In light of the drastic exhaustion of natural resources and increased environmental pollution, to promote the use of green products, the government subsidises them and levies taxes on non-green ones. This paper considers a dual-channel supply chain with a manufacturer selling a green product online and a substitutable non-green product offline using a retail channel. The price differential splits the market into two segments. The stochastic linear demand is modelled as a function of prices, green quality level, and sales effort level, considering government tariffs and demand leakage. A centralised decision model is investigated for the case of uniform distribution and distribution-free demand. It is shown that the green quality level and the total supply chain profit increase with an increase in demand leakage. Also, it reveals that with an increment in government subsidy and tax, the total supply chain profit and green quality level are higher in uniform distribution. [Submitted: 20 April 2023; Accepted: 9 October 2023]
  Keywords: dual-channel supply chain; government tariffs; cannibalisation; uniform distribution; distribution-free.
  DOI: 10.1504/EJIE.2025.10061256
   
  
• Improving the Quality of Production through the Six Sigma Method in a Textile Business  
  by İzzettin Hakan Karaçizmeli 
  Abstract: This study aims to reduce seam mark defects to improve the quality in a cotton fabric manufacture business by using the Six Sigma method. The DMAIC steps were followed. First, potential root causes were identified through brainstorming. Causes related to sewing thread, sewing machine settings and operator mistakes came to the fore in the brainstorming. Then, a data collection plan was devised, and the necessary data were collected. The analysis of studies on root causes were conducted by using the collected data. It was found that sewing thread, one of the raw materials used, played a role in increasing the defects. Furthermore, it was found that sewing operators needed training, and the settings of the machines should be improved. For solving these problems, the improvements were put into use. Finally, necessary monitoring plans were made. The results of the study indicated that the seam mark defects were reduced by 63%. [Submitted: 23 May 2023; Accepted: 16 October 2023]
  Keywords: quality; textile; Six Sigma; process improvement; seam mark.
  DOI: 10.1504/EJIE.2025.10061430
   
  
• Shift scheduling and rostering with same shift-type and weekend-off fairness constraints in call centres  
  by Ruicheng Wang, Yue Xu, Xiuli Wang 
  Abstract: Based on the actual operational situation of call centres, this paper incorporates the constraints of the same shift-type within a week and the fairness of weekends-off into scheduling. Utilising the progressive decomposition structure of the same shift-type constraint, this paper constructs an integer programming model for multi-week scheduling optimisation problem of call centre agents. We first analyse the maximum lower bound of the problem and prove the optimality of its relaxation problem. Then we propose a two-stage algorithm which combines a constructive heuristic with neighbourhood search incorporating simulated annealing. Experimental results show that the integer programming model is only suitable for achieving optimal solutions for small-scale problems, while our two-stage algorithm can obtain (sub-)optimal solutions for large-scale problems. The impact of employment policy on labour costs is also discussed. [Submitted: 21 March 2023; Accepted: 12 November 2023]
  Keywords: call centre; shift scheduling; rostering; integer programming; optimal algorithm; heuristic algorithm; neighbourhood search; weekend-off fairness; same shift-type; operations management.
  DOI: 10.1504/EJIE.2025.10061821
   
  
• A Multi-Objectives Optimization Model for the Joint Design of Statistical Process Control and Engineering Process Control  
  by Salih Osman Duffuaa, Omar Dehwah, Abdul-Wahid Al-Saif, Anas Alghazi, Awsan Mohammed 
  Abstract: Statistical process control and engineering process control are two methodologies used for process control and improvement. These technologies have existed independently of one another. Consequently, this research aims to simultaneously design statistical process control and engineering process control utilising multi-objectives optimisation. In this research, statistical and economic criteria are used to construct statistical process control and engineering process control jointly. To solve the developed model, an effective heuristic method is proposed. A numerical example is used to illustrate the significance of combining the two techniques. The results showed that the proposed solution can obtain the Pareto efficient solutions. This will help decision-makers to select the best solution based on their preferences. In addition, the findings indicated that the expected income values range between $172.0839 and $177.2175, and the Taguchi cost values vary between $4.469333 and $7.907547. On the other hand, the power values range between 0.91373 and 1. Moreover, the results revealed that as the Taguchi cost increases the expected income will increase and the power will decrease. Furthermore, sensitivity analysis is performed to determine the effect of variables in the model. The sensitivity analysis showed that the power of the chart decreases as the value of sigma is raised. [Submitted: 31 July 2023; Accepted: 26 November 2023]
  Keywords: statistical process control; SPC; engineering process control; EPC; multi-objectives; control charts; process monitoring.
  DOI: 10.1504/EJIE.2025.10061955
   
  
• An Agile Optimization Algorithm for the Multi-Source Team Orienteering Problem  
  by Mattia Neroni, Javier Panadero Martinez, Elnaz Ghorbani, Majsa Ammouriova, Angel A. Juan 
  Abstract: In the team orienteering problem (TOP), a fixed fleet of vehicles have to collect rewards by visiting customers. Typically, all vehicles depart from a source depot and end in a sink depot. Also, each vehicle has a limited driving range, so not all customers can be visited. The goal is then to select the set of customers to be visited, and the corresponding routes to do it, such in a way that the total reward collected is maximised while respecting the aforementioned constraints. This paper explores a TOP variant with multiple source depots and where real-time solutions need to be provided, i.e., computation times need to be in the order of milliseconds even for mid-sized instances with hundreds of customers. To deal with this challenge, and taking into account that the problem is NP-hard, we propose an 'agile' optimisation algorithm that is based on a biased-randomised heuristic. Our approach can be applied in realistic and dynamic scenarios where vehicles need to recompute their routes in real-time, as vehicles are in-route, new customers appear, and some existing customers are not available anymore. [Submitted: 20 May 2022; Accepted: 31 December 2022]
  Keywords: agile optimisation; biased-randomised heuristics; team orienteering problem; TOP; dynamic scenarios.
  DOI: 10.1504/EJIE.2025.10062276
   
  
• Research on Pricing Strategy of Closed-loop Supply Chain Based on PIR and Recovery Effort  
  by Jun Yao, Dongyan Chen, Hui Yu 
  Abstract: Waste products bring opportunities and challenges to remanufacturing. A Stackelberg game model based on PIR and recycling effort is constructed to compare and analyse the optimal pricing, product demand and system benefits of the closed-loop supply chain with or without PIR and recycling efforts. The results are as follows: compared with the without of PIR and recycling effort, manufacturers can lower the retail price of their products under PIR and recycling efforts to promote the increase of product demand and system total revenue. When the PIR level and the cost saving per unit of remanufactured product are constant, the larger the recycling amount of waste products is, the more total cost will be saved. It can be seen that recycling efforts will indirectly affect the level of PIR. When the input cost coefficient of PIR meets certain conditions, the manufacturer can obtain the income brought by PIR. [Submitted: 14 December 2022; Accepted: 7 November 2023]
  Keywords: process innovation for remanufacturing (PIR); recovery efforts; closed-loop supply chain; Stackelberg game; pricing strategy.
  DOI: 10.1504/EJIE.2025.10062351
   
  
• Optimization of a Multi-Item Inventory model for deteriorating items with budget constraint, time-dependent holding costs, and two-level quantity discount: A comparison  
  by Mahdi Karimi, Seyed Jafar Sadjadi 
  Abstract: Considering the increasing number of perishable goods, it is necessary to study the inventory control of these items. Previously, due to the difficulty of the models and the need for solution methods, many fundamental assumptions were ignored. This article presents a multi-item economic order quantity model for deteriorating items. This paper's novelties are using dynamic programming, adding both budget and capacity constraints, and some realistic assumptions to the model. This study allows shortages with partial backlogging, and a two-level discount is available. Also, we investigated the unspent budget elsewhere to increase the total income. The greedy search and metaheuristic methods were used to compare the results with the primary method. The results show that the proposed dynamic programming can solve the problem and surpass metaheuristic methods in precision and running time (for small cases). A sensitivity analysis was conducted and resulted in some managerial and theoretical insights.
  Keywords: inventory control; economic order quantity; deteriorating items; budget constraint; capacity constraint; dynamic programming.
  DOI: 10.1504/EJIE.2025.10062773
   
  
• A mixed integer programming model and a hybrid VNS/TS algorithm for GVRP with the heterogeneous fleet, time windows, and vehicle selection  
  by Emine AKYOL ÖZER, Melis ALPASLAN TAKAN, Tugba Sarac 
  Abstract: The green vehicle routing problem (GVRP) is a logistical problem considering environmental effects. Existing GVRP studies considered important constraints such as time windows (TW) or heterogeneous fleets (HF), but mostly, they assumed that there is an available fleet where all vehicles can be used. However, some companies build their fleets using rented cars by selecting the vehicle numbers and types. Therefore, we focus on GVRP with the HF, TW, and vehicle selection to minimise travel, rental, and emission costs. A MIP model, and a hybrid algorithm combining variable neighbourhood search with the tabu search algorithm are proposed. The performance of the algorithm is demonstrated by using the modified Solomon test instances. The proposed algorithm could produce high-quality solutions within a short computation time. In addition, an average improvement of 45.49% and 16.69% are achieved respectively compared to the first scenario and the second scenario where the vehicles are held constant. [Submitted: 6 February 2023; Accepted: 9 January 2024]
  Keywords: heterogeneous fleet green vehicle routing problem; HFGVRP; green vehicle routing problem with time window; GVRPTW; vehicle selection; variable neighbourhood search; VNS; tabu search; TS.
  DOI: 10.1504/EJIE.2025.10063127
   
  
• Lagrangian-Based Solutions for the Multi-Level Production-Inventory Problem in Iron and Steel Production with Reverse Logistics  
  by Guoli Liu 
  Abstract: This research deals with the production-inventory problem originating from the ironmaking production system in Shanghai Baoshan Iron and Steel Complex. A mixed integer programming (MIP) model based on the minimisation of total related costs including production/purchasing costs, inventory costs and setup costs is proposed to determine the production and inventory quantities of all materials in each time period under material-balance and capacity constraints. To solve the problem, a decomposition approach based on Lagrangian relaxation (LR) is developed. A solution property is introduced to speed up the solving process. Heuristic strategies are applied to improve the upper bound. In order to further improve the quality of the solutions, an alternative Lagrangian relaxation algorithm based on variable splitting is derived. A detailed numerical evaluation based upon the actual production data from Baosteel is performed. The computational results reveal that the proposed algorithms can obtain good quality solutions within a reasonable time. [Submitted: 6 February 2023; Accepted: 25 February 2024]
  Keywords: combinatorial optimisation; Lagrangian relaxation; reverse logistics; production-inventory planning.
  DOI: 10.1504/EJIE.2025.10063416
   
  
• Measuring Modularity on Manufacturers' Distribution Channel Strategies: Direct selling, Reselling or Agency Selling  
  by Qinyu Song, Meng Yang, Yaodong Ni 
  Abstract: In recent years, consumers not only pursue cost-effective products but also begin to attach importance to individual customization. This paper investigates the effects of the modularity level on a manufacturer's three channel strategies. We find that the modularity level under reselling and agency selling is lower than that under direct selling. Considering modularity, the retail price under agency selling is lower than that under direct selling. Therefore, when the consumer pays attention to the modular design, if the commission fee is high (low), the manufacturer will adopt the direct selling (agency selling) model. However, when the consumer's customization concern is weak, the manufacturer prefers the reselling format. In addition, referring to dual distribution channels, the manufacturer may authorize the modular design to the retailer when the modular-sensitive the parameter is high. [Submitted: 29 August 2023; Accepted: 5 March 2024]
  Keywords: Distribution channel; Modularity; Agency selling; Reselling; Game theory.
  DOI: 10.1504/EJIE.2025.10064026
   
  
• Design and development of an optimization model and simheuristic framework for the on-demand delivery problem with driver-experience-based stochastic travel time  
  by Shuzhu Zhang, Bingbing Qiu, Jinyue Tian 
  Abstract: In this research, we investigate an on-demand delivery problem in city logistics, in which delivery requests from online customers are received in real-time and delivery services are conducted in short time. A multi-stage stochastic vehicle routing optimisation model is proposed, which incorporates two unique features arising from city logistics delivery, i.e., driver experience and stochastic travel time. In practice, the estimated travel time is indeed affected by the driver experience and can be gradually improved as drivers learn from accumulative delivery experience. A simheuristic framework is developed to handle the proposed model, in which an improved adaptive large neighbourhood search is designed for searching promising solutions with deterministic travel time, and Monte Carlo simulation is leveraged to assess the solution qualities and facilitate the searching process in stochastic scenarios. Computational experiments demonstrate that the proposed simheuristic framework can tackle the on-demand delivery problem with satisfactory performance. [Submitted: 22 November 2023; Accepted: 13 April 2024]
  Keywords: on-demand delivery; stochastic travel time; simheuristic framework; adaptive large neighbourhood search; driver experience.
  DOI: 10.1504/EJIE.2025.10064385
   
  
• A Sustainable Hub Location-Allocation Model considering the Inspection of Defective Wagons in the Rail Freight Network  
  by Bahareh Sohrabi Pirdousti, Amir Hossein Sheikh Azadi, Ali Heidari, Mohammad Khalilzadeh, Omid Kebriyaii 
  Abstract: The increasing demand for rail transport necessitates an effective transportation network design for the shipment of goods with minimum cost and time. Since the breakdown of wagons is a main delay factor in rail transportation, the maintenance and repairs of defective wagons becomes prominent. In this study, main stations are considered as hubs, and hubs are places where defective wagons are collected. For this purpose, a robust multi-objective mathematical model is proposed to minimise transportation costs considering customer demand. Also, the model seeks to minimise the total transportation time and emissions. The AEC method is exploited to solve and validate the proposed model. Moreover, the sensitivity analysis is performed to demonstrate the effect of changing the main parameters on the outcomes. The results show that repairs and maintenance can affect the capacity. Also, the findings demonstrate the applicability and validity of the proposed model in the railway sector. [Submitted: 29 May 2023; Accepted: 16 January 2024]
  Keywords: railway transportation; sustainability; hub location-allocation; maintenance; repair; augmented epsilon constraint; AEC.
  DOI: 10.1504/EJIE.2025.10064728
   
  
• Designing a Reverse Biomass Supply Chain Network under Uncertainty Conditions using Robust Programming and Lagrangian Relaxation Algorithm  
  by Alireza Hamidieh, Bahareh Akhgari Rik 
  Abstract: Researchers have studied solutions for reducing pollution and resource waste caused by increases in environmental pollution and resource waste. Moreover, increased productivity, reduced energy generation costs, decreased dependence on fossil fuels and use of biogas in supply chain networks have attracted interest from many industrialists. This research designed a biomass-based reverse supply chain network under conditions of uncertainty about capacity, demand and raw material quality that focused on increased profits and reduced biomass waste. For this purpose, a two-stage stochastic mixed-integer programming model was developed and robust optimisation was used to cope with the uncertainty about the parameters of quality, demand and capacity. In addition, a Lagrangian relaxation (LR) algorithm for simplification of the complicated constraints of the NP-hard problem was developed that could solve large-scale problems with a competitive convergence rate. [Received 6 July 2022; Accepted 4 December 2023]
  Keywords: biomass; Lagrangian relaxation; quality; robust; supply chain.
  DOI: 10.1504/EJIE.2025.10064788
   
  
• Designing an Enhanced Acceptance Sampling Strategy with the Process Loss Index  
  by Armin Darmawan, Chien-Wei Wu 
  Abstract: To reconcile the differences between loose and stringent models and address product specifications sensitive to target value variations, a process loss index Le was introduced. This index assesses process capability by incorporating the concept of the quality loss function. Some researchers have integrated this index into variables sampling plans. In particular, Repetitive Group Sampling Plans (RGSP) offer cost advantages over single sampling plans, but their infinite sampling nature might lead to inefficiencies. To address this, our study introduces a modified RGSP with an adjustable lot disposition mechanism based on the process loss index. We establish an optimisation model to minimise the anticipated number of sample items, considering quality and risk constraints. Performance is compared to conventional methods using metrics such as average sample number, operating characteristic curve, and average run length. Ultimately, a practical demonstration is provided through an example to illustrate and validate the feasibility of the proposed plan. [Submitted: 22 January 2024; Accepted: 17 May 2024]
  Keywords: acceptance sampling; average sample number; quality loss; quality assurance; operating characteristic function.
  DOI: 10.1504/EJIE.2025.10064829
   
  
• Assessment of equipment financial performance in overall equipment effectiveness metric for gauging manufacturing equipment criticality  
  by CHEN FUNG LIEW, Joshua Prakash, Kok Seng Ong 
  Abstract: This paper introduces equipment cost effectiveness, a metric for evaluating the financial performance of equipment in manufacturing. While overall equipment effectiveness is widely used to assess operational performance, its limited focus on financial aspects necessitates a more comprehensive approach. Equipment cost effectiveness addresses this limitation by quantifying the wastage of equipment acquisition cost and maintenance cost at any overall equipment effectiveness level. Real-world data from the medical device, tyre flap, and semiconductor industries validate equipment cost effectiveness through correlation analysis, revealing a negative relationship between overall equipment effectiveness and both equipment acquisition cost and maintenance cost. Equipment cost effectiveness provides a holistic evaluation of equipment, enabling better decision-making and cost optimisation. By bridging the gap between operational and financial evaluations, equipment cost effectiveness offers valuable insights for enhancing equipment efficiency and resource allocation in manufacturing operations. [Received: 22 April 2023; Accepted: 10 November 2023]
  Keywords: overall equipment effectiveness; OEE; equipment cost effectiveness; ECE; equipment acquisition cost; maintenance cost; improvement cost.
  
  
• Dual-Channel Selection Strategy of Green Supply Chain Considering Online Retail Platform under Different Forms of Government Subsidies  
  by Xiaoqing Zhang, Xigang Yuan, Wang Yongjian, Dalin Zhang 
  Abstract: To accelerate the sustainable development of green supply chains (GSCs), governments adopt different forms of subsidies, including research and development (R&D) cost subsidies and unit production subsidies, and manufacturers develop different dual-channel structure models based on these subsidies. We build one three-level game analysis model including a government, a manufacturer, and an online retail platform and solve it using the backward induction method, and we explore the optimal dual-channel structure model of GSCs. We find that when the manufacturer better controls the cost of green R&D, the unit production subsidy is better for producing green products and can also make the online retail platform more profitable. When the government offers the R&D cost subsidy, the manufacturer should select the online direct and online reselling channel structure model. In contrast, when offering the unit production subsidy, the manufacturer should adopt the online direct and online reselling channel structure model under certain conditions. Furthermore, when both the cost ratio of technology R&D and the marginal revenue rate of environmental improvement are lower than a certain threshold, the unit production subsidy is a better strategy for the government. Otherwise, we suggest that the government adopt an R&D cost subsidy strategy. [Received: 30 November 2022; Accepted: 17 December 2023]
  Keywords: green supply chain; GSC; government subsidy; online direct channel; online reselling channel; online agency channel.
  DOI: 10.1504/EJIE.2025.10065592
   
  
• Discrete Time/Cost Trade-off Project Scheduling Problem with Tardiness Bounds  
  by Ozlem Akbudak, Gulsah Karakaya, Meral Azizoglu 
  Abstract: We consider a discrete time/cost trade-off problem with due dates and an upper bound on the total tardiness. Our motivation stems from information technology projects held in the Ministry of Health in Turkey. Our primary objective is to minimise the total cost while obeying the total tardiness bound. We formulate the problem as a mixed integer linear program and propose a heuristic approach that leverages the optimal solutions from the linear programming relaxation of the model. To assess the performances, we conduct tests on instances from relevant literature and the Ministry of Health projects, and report favourable results. We employ the optimal solutions to the constrained optimisation problem to generate the exact non-dominated objective vectors' set with respect to total tardiness and total cost. Additionally, we present an evolutionary algorithm to find an approximate set. The algorithms are demonstrated using the projects of the Ministry of Health in Turkey. [Submitted: 5 February 2023; Accepted: 10 September 2023]
  Keywords: discrete time/cost trade-off project scheduling problem; mixed integer linear program; heuristic approach; evolutionary algorithm.
  DOI: 10.1504/EJIE.2025.10066256
   
  
• Integrated Assortment, Shelf Space, and Inventory Decisions in Retail considering Product Deterioration with Elasticity and Positioning Effects  
  by Davide Castellano, Mosè Gallo 
  Abstract: This paper investigates a problem faced by retailers when selling multiple products and specifically the decisions related to product assortment, shelf-space planning, inventory replenishment, and storage capacity allocation. Products deteriorate while in stock and are jointly replenished. Additionally, their demand is influenced by elasticity and positioning effects. The retailer's objective is to maximise the profit by determining the optimal ratio between the surfaces assigned to the backroom facility and the display area, the optimal product assortment, the optimal space assignment and allocation, and the optimal coordinated inventory replenishment policy. A hybrid solution procedure, including a genetic algorithm, is proposed. Among the findings, it was observed that as the decay rate increases, it is preferable to reduce the surface dedicated to the backroom facility. In fact, to mitigate the negative impact of deterioration on profit, it appears desirable to reduce the order quantity and expand the product assortment. [Submitted: 16 January 2024; Accepted: 29 July 2024]
  Keywords: inventory; deterioration; assortment; shelf space; optimisation; retail.
  DOI: 10.1504/EJIE.2025.10066342
   
  
• Exploring the Role of Influential Scholars in Maritime and Port Logistics Systems  
  by Andro Dragovic, Nenad Zrnic, Branislav Dragovic, Maxim A. Dulebenets 
  Abstract: There is no annual ranking for top scientists in the area of maritime and port logistics systems (MPLSs), such as in the area of physics or top 10 most influential mathematicians. Therefore, the main aims of the present study are to offer the academic community more visibility of the influential research and highlight the scholars whose relevant bibliometric indexes are higher than average. A systematic, scientific, and fair approach based on very well-known bibliometric indexes is conducted to identify the most influential scholars. This provides possibilities for a rigorous comparative analysis, as well as assessment of scholars' scientific outputs. The internal database includes a total of 8,774 documents that were comprehensively analysed. All the obtained results are reproducible and verifiable. If this approach omitted some credible scholars, it should not be considered as a judgment of the merit of their scientific output. [Submitted: 14 February 2024; Accepted: 15 July 2024]
  Keywords: influential scholars; scientific output; word cloud analysis; conceptual structure analysis.
  DOI: 10.1504/EJIE.2025.10066366
   
  
• Strategic Insights: A System Dynamics Approach to Analyse Sustainability and Cost Efficiency in Indian Freight Transportation Scenarios  
  by Firoz N, Vinay Panicker 
  Abstract: Freight transportation decarbonising is one of the key challenges in climate change mitigation efforts. The modal shift is considered a widely accepted effective strategy towards reducing carbon emissions in transportation. The main focus of this paper is to analyse the modal shift policy towards freight transport decarbonisation in India. A carbon tax on road transport was proposed to promote the transport to low carbon transport modes. A system dynamics model was developed to analyse the time-dependent complex freight transportation system with the introduction of a carbon tax under three scenarios. The optimal modal share can be obtained in a fast-change scenario by 2042, with a significant reduction of 37% in carbon emission and 4% in logistics cost. The fast change scenario recommends the modal transition at a rate of 11.5%. These findings will support the government for proactive measures for a swift transition in line with the fast-change scenario. [Submitted: 12 October 2023; Accepted: 6 August 2024]
  Keywords: freight transport; decarbonisation; modal shift; carbon tax; system dynamics; India.
  DOI: 10.1504/EJIE.2026.10066397
   
  
• Two-stage Stochastic Robust programming based on MOPSSCA for Flight Crew Scheduling Problem  
  by Parvaneh Zeraati Foukolaei  
  Abstract: The main purpose of providing the mathematical model is to achieve the optimal flight schedule, optimal fleet allocation, optimal aircraft routing, and crew scheduling to reduce the total costs of flights and the amount of fuel consumed in all flights. Due to the uncertainty of the flight of the planes at the appointed time and the presence of numerous delays, modelling in different scenarios was presented based on the probability of the event. The calculation results of solving the numerical example with the epsilon method of the limit showed that the change in the flight schedule of the planes and the presence of delay in it leads to an increase in the flight costs and, as a result, leads to an increase in the amount of fuel consumed. In this article, a new hybrid algorithm named MOPSSCA was introduced, which has achieved near-optimal solutions with a maximum error of 2%.
  Keywords: flight crew scheduling; two-stage stochastic robust programming; MOPSSCA; crew scheduling; flight routing.
  DOI: 10.1504/EJIE.2025.10066439
   
  
• Influence Index Analysis of Inland Waterway Ports Along the Yangtze River  
  by Yanjie Zhou, Liping Luo, Qian Qian Zhao, Haonan Chen, Zehao Qian, Songle Leng 
  Abstract: Inland waterway ports located along the inland waterway have different functions compared with seaports that cannot use the previous method adopted for seaports to calculate the inland port influence index. To make a comprehensive analysis, this paper considers multiple years' worth of factors, including the facility of inland ports, urban economic and traffic factors. This paper introduces a group entropy weight method to evaluate the inland port influence index considering the multiple years' data. A visualization tool integrated with the group entropy weight method is developed to analyse the port performance index automatically. 27 inland waterway ports along the Yangtze River are considered as a case study for analysing their influence index. The management insights of the dynamic change of inland waterway port ranks are also discussed. [Submitted: 4 March 2024; Accepted: 28 June 2024]
  Keywords: Port performance index; Yangtze River; Inland waterway ports; Port ranking.
  DOI: 10.1504/EJIE.2025.10066546
   
  
• A Unified Generalised Process Capability Index and its Applications to Logistic-Exponential Distributed Characteristic  
  by Mahendra Saha, Amartya Bhattarchya, Sukanta Pramanik, Sudhansu Shekhar Maiti, Arindam Gupta 
  Abstract: The introduction of the process capability index has made it possible for industries to evaluate process performance and assess how well the final product meets consumer expectations. In this article, we take into consideration the six most popular estimation techniques, namely the maximum likelihood, least square, weighted least square, percentile, Cram`er-von-Mises, and maximum product of spacing techniques, in order to estimate the parameters and the new unified measure of the generalised process capability index, denoted as Cpy(u, v) for the logistic-exponential process distribution. Extensive simulations are carried out to investigate the performances of these considered classical estimation methods in terms of their respective biases and mean squared errors. Additionally, we contrast the results of three bootstrap confidence intervals of Cpy(u, v) in terms of average widths and coverage probabilities: standard bootstrap, percentile bootstrap, and bias-corrected percentile bootstrap. Two data sets related to the electronic industries are re-analyzed in order to show the applicability of the suggested methodologies.[Submitted: 28 December 2022; Accepted: 17 October 2023]
  Keywords: Monte-Carlo simulation; point and interval estimation; unified measure of process capability index.
  DOI: 10.1504/EJIE.2025.10066767
   
  
• Optimisation of the Length of Global Supply Chain for Decarbon Purpose  
  by Weichen Gao, Shanhua Wu, Hongxiang Feng, Zhongzhen Yang 
  Abstract: Economic globalisation has boosted production and consumption, improving living standards but increasing demand for long distance trade transportation and carbon emissions. This paper maps global export cargo turnover as the length of the global supply chain (SCL) and introduces a method to calculate each country's carbon emissions based on consumer responsibility. The method considers emissions from manufacturing, transportation and technological disparities of finished goods between countries. To minimise total costs, including carbon costs, we optimise the SCL. Empirical analysis of by taking China, the USA, Japan, European Union and ASEAN as a small and closed area shows a 43.69% reduction in optimised SCL. The USA contributes 59.31% of this reduction, 8.5 times that of China and 18 times that of ASEAN. Under this optimisation, total carbon emissions from manufacturing will drop by 6.62%, with China experiencing the largest decrease (25.23%) and the USA the largest increase (15.91%). [Received: 24 February 2024; Accepted: 4 September 2024]
  Keywords: global supply chain; economic globalisation; international trade transportation; carbon emissions; finished goods.
  DOI: 10.1504/EJIE.2025.10067170
   
  
• Simulation-Based Ripple Effect Modelling in the Supply Chain: a Network Perspective  
  by Yueran Zhang, Zhanwen Niu, Kaixuan Hou 
  Abstract: This research investigates the ripple effects of supply chain disruptions across supply chain echelons and identifies vulnerable network characteristics. Utilising simulation methods, the study analyses the impact of disruption scale, propagation extent, and delay on supply chain performance. Employing AnyLogistix software, the study evaluates ripple effects across four different network structures under disruption scenarios resembling the COVID-19 pandemic, characterised by prolonged impacts on supply, demand, logistics, and uncertain recovery times. Comparative analysis across network structures reveals insights into recovery strategies, highlighting the influence of network characteristics on performance outcomes. The findings demonstrate that both disruption severity and propagation delay significantly affect supply chain performance, with high connectivity and betweenness centrality enhancing resilience during prolonged disruptions. This study contributes to the literature by integrating ripple effect assessment with network topology considerations, providing both theoretical insights and practical guidance for optimising supply chain design and management in the post-COVID era. [Submitted: 8 February 2024; Accepted: 3 September 2024]
  Keywords: disruption; ripple effect; supply chain; simulation; resilience; network structure; network characteristics.
  DOI: 10.1504/EJIE.2025.10067300
   
  
• Optimising Logistics Packaging and Replenishing Policies for Deteriorating items in E-Commerce Environments  
  by Tien-Yu Lin 
  Abstract: This paper develops an instantaneously deteriorating inventory model for an e-commerce environment wherein the retailer employs an improved logistics packaging policy to reduce the rate of damage to goods in transit. Because of the difficulty in finding a closed-form solution, an efficient algorithm has been developed to find the optimal solution for the proposed model. The theoretical results show that the deteriorating rate could impact the optimal solution and the average total profit. The replenishment time for the proposed model with return rate is shorter than that for the traditional EOQ model. Numerical examples illustrate the proposed model and algorithm. Moreover, sensitivity analysis illustrates the effects of four parameters of importance (i.e., set-up cost, demand rate, holding cost, and deteriorating rate) on the optimal strategy. The discussion of numerical and sensitivity analysis results provide some managerial insights. [Submitted: 6 June 2023; Accepted: 15 February 2024]
  Keywords: inventory; logistics packing policy; deterioration; e-commerce; replenishing policy.
  DOI: 10.1504/EJIE.2025.10067748
   
  
• A Hybrid Particle Swarm Optimisation Algorithm for Multi-Resource Constrained Flexible Job Shop Scheduling Problem with Transportation  
  by Deling Yuan, Zexi Yang 
  Abstract: In the flexible job processing environment, there exists an insufficient optimisation of spatial and transportation resources. To effectively solve the multi-resource constrained flexible job shop scheduling problem with transportation, it is imperative to consider factors such as the capacity of transportation equipment, limitations of the transportation equipment temporary storage area and job temporary storage area. This article focuses on the coordinated scheduling of processing and transportation tasks, aiming to minimise the makespan and the total equipment running time. A hybrid particle swarm optimisation algorithm (NHPSO) is designed, incorporating genetic algorithm's (GA) crossover and mutation functions to preserve particles' genetic information while enhancing global search capabilities. The simulated annealing (SA) mechanism is also included to boost early-to-mid-stage optimisation ability and broaden solution search range. A neighbourhood search strategy based on the critical chain concept is developed in three evolutionary directions to enhance algorithm effectiveness without getting stuck at local optimums. Finally, the convergence ability and effectiveness of the proposed algorithm are verified by experiments. [Submitted: 4 November 2023; Accepted: 20 July 2024]
  Keywords: flexible job shop scheduling; FJSP; limited resources; particle swarm optimisation; neighbourhood search; transportation.
  DOI: 10.1504/EJIE.2025.10067782
   
  
• Characterising the Cost of Additive Manufacturing: Demand Volatility and Absence of Inventory  
  by Ageel Alogla, Martin Baumers, Christopher Tuck 
  Abstract: This paper explores the impact of Additive Manufacturing (AM) on supply chain cost-effectiveness for products with volatile demand. It specifically assesses how AM adoption affects inventory and stockout costs through an exploratory simulation. The study compares the unit costs of AM with Injection Moulding (IM) and a combination of both. Results indicate that using AM alongside IM is cost-effective only with high stockout penalties. Without such penalties, IM alone proves to be the most economical option. This research provides insights into strategic production decisions in supply chains with fluctuating demand. [Submitted: 13 December 2023; Accepted: 4 September 2024]
  Keywords: Additive Manufacturing; Discrete-event Simulation; Demand Uncertainty; Design of Production Systems; Bullwhip Effect.
  DOI: 10.1504/EJIE.2025.10067932
   
  
• Performance analysis for a dual-crane automated storage and retrieval system  
  by Letitia M. Pohl, Mahmut Tutam 
  Abstract: Automated storage and retrieval systems (AS/RSs) were first implemented in the 1960s and continue to be installed today, albeit with dramatically evolved technologies. When compared to more manual systems, an AS/RS has the potential to dramatically reduce labour costs, with increased productivity, higher storage density, better order and inventory accuracy, and improved product security. Despite the advantages and widespread implementations, the typical unit-load, single-crane AS/RS is still often characterised by high initial costs and limited maximum throughput. This paper proposes a new design that uses two cranes in one aisle, where the cranes operate cooperatively to increase throughput, thereby allowing a facility that is at capacity to be retrofitted without a complete equipment upgrade and without the need for a new facility. We model travel time of the two cranes and develop system throughput equations. Significant throughput improvement is possible with the new design over a comparable single-crane AS/RS. [Received: 12 September 2022; Accepted 17 July 2023]
  Keywords: unit-load warehouse; automated storage and retrieval systems; AS/RS; dual-crane; optimal buffer position; throughput models.
  DOI: 10.1504/EJIE.2025.10059498
   
  
• A multi-period inventory model with price, time and service level dependent demand under preservation technology investment  
  by Sudarshan Bardhan, Indrani Modak, Bibhas Chandra Giri 
  Abstract: Price and time are two important parameters having significant impact on market demand, especially for fashion items, newly launched electronic products, etc. After-sale service facility offered by the retailers is seen to boost demand while investing in preservation technology reduces product spoilage. All these issues are taken into consideration while developing a multi-period inventory model where market demand depends on all three of the above-mentioned factors. The replenishment cycles are all of equal length, but due to the time-dependent nature of demand, the stock-in (and consequently stock-out) periods in the cycles are allowed to vary. The policy of planned shortages followed by replenishment in each cycle is adopted and seen to be fruitful indeed. Learning effect in holding and ordering costs are taken into account. The effects of limited capital and warehousing space are investigated. Numerical examples are employed to demonstrate the developed model and gain managerial insights from it. [Received: 23 December 2022; Accepted: 3 August 2023]
  Keywords: price dependent demand; learning effect; preservation technology; service level; multi-period inventory model.
  DOI: 10.1504/EJIE.2025.10059500
   
  
• Compact MILP models for double row layout problem with pairwise clearance  
  by Richard Alaimo, Churlzu Lim 
  Abstract: Double row layout problem (DRLP) seeks for an optimal arrangement of departments along both sides of a central corridor to minimise the total material flow cost. This study considers a variant of DRLP where pairwise minimum clearance requirements between departments are enforced when they are assigned to the same side. This problem accounts for additional interaction that exists between departments during the layout planning process. Two mixed-integer linear programming formulations are proposed with the motivation that using fewer binary variables compared to the existing formulation in the literature helps reduce the solution time. Noting the NP-hardness of the problem, symmetry-breaking constraints are investigated in an effort to further alleviate the computational burden. The efficacy of the proposed models is demonstrated via a computational study using a set of test problem instances. [Received: 9 February 2022; Accepted: 11 August 2023]
  Keywords: facility layout; double row layout problem; mixed-integer linear programming; combinatorial optimisation; clearance requirements.
  DOI: 10.1504/EJIE.2025.10060235
   
  
• Sensitivity comparison of control charts under MAD shift detector using the rank set sampling scheme  
  by Nadia Saeed, Moustafa Omar Ahmed Abu-Shawiesh 
  Abstract: In this article, the sensitivity comparison of the standard Shewhart S-control chart is done with the MAD-control chart under the rank set sampling (RSS) scheme. The median absolute deviation (MAD) from the sample median is considered a robust estimator for the outlier's detection relative to the sample standard deviation (SD). Extensive simulations are conducted to evaluate the control charts' performance using both estimators under the RSS scheme for different sample sizes. The values for the out-of-control average run length (ARL₁), standard deviation of run length (SDRL) and percentile points under different shifts are used as performance measures. On the basis of Monte Carlo simulations, it is revealed that as the shift gets large; control charts are equally effective to detect it while for small shifts, the suggested robust MAD-control chart performed well and better. A real-life dataset is analysed to support our findings from the simulation study for illustrative intents justified that the MAD robust estimator is a better outlier detector. [Received: 26 November 2022; Accepted: 11 August 2023]
  Keywords: rank set sampling; RSS; control chart; shift detector; outliers; median absolute deviation; MAD; percentile points; average run length; ARL.
  DOI: 10.1504/EJIE.2025.10060058
   
  
• Optimum design of an efficient variables sampling system for validating process yield with Six-Sigma quality requirement and creation of a cloud-computing too  
  by Chien-Wei Wu, Ming-Hung Shu, Bi-Min Hsu, To-Cheng Wang 
  Abstract: Six Sigma quality levels have become well-known process yield targets in supply chain channels. To meet this high-yield requirement, the variables tightened-normal-tightened sampling system (VTSS) operates a dynamic rule-switching strategy between sampling plans, becoming a flexible and economical method for practitioners to verify products. Existing VTSSs based on the process yield index are only designed to adjust sample sizes in tightened and normal inspections. In this paper, a VTSS with alterable acceptance standards is developed. We derive the proposed VTSS's operating characteristic function and integrate it with the producer's and consumer's yield-and-risk requirements to construct an optimisation model for the determination of the optimal system design. After conducting a series of investigations into the performance between the proposed VTSS system with the existing VTSS system with alterable sample sizes, we concluded the proposed VTSS could reduce the average sample size by more than 50% and has a steeper operating characteristic shape, which indicates superior cost-efficiency and discriminative power. Moreover, we designed a cloud-computing tool to build an open-access platform to help practitioners implement our proposed VTSS easily and efficiently. Finally, the practicality and applicability of the proposed VTSS are illustrated through an industrial case. [Received: 15 December 2022; Accepted: 25 August 2023]
  Keywords: Six Sigma; process yield; lot sentencing; alterable acceptance standard ; tightened-normal-tightened sampling system.
  DOI: 10.1504/EJIE.2025.10059660