International Journal of Simulation and Process Modelling (7 papers in press)

Regular Issues

• A novel variable drive modelling approach for general framework of chemical production scheduling  
  by Yuandong Chen, Jinhao Pang, Zhen Jiang, Yuchen Gou, Dewang Chen 
  Abstract: In this paper, we present a modelling approach named as variable drive modelling (VDM) to develop general modelling framework of chemical production scheduling. VDM builds model from variable (i.e., variable-based), while the traditional method building model from rule aspect (i.e., rule-based) with constraint blocks such as allocation constraints, mass balance, capacity constraints and operation rule constraints. In this paper, we analyse three shortcomings of the traditional rule-based model building method. A novel scheduling time axis is presented, while the confusing position of variables at time axis can be avoided. A systematic method to define variables and description rules of driving functions are given. At last, a crude oil scheduling case was given out to illustrate how to implement this approach. The results show less variable numbers, less constraints, less branching nodes, and more less solution time of the proposed approach against the existing model.
  Keywords: simulation and modelling; scheduling; variable drive modelling; VDM; chemical processes; refinery.
  DOI: 10.1504/IJSPM.2024.10063225
   
  
• A fusion model of gated recurrent unit and convolutional neural network for online ride-hailing demand forecasting  
  by Xijin Cui, Mingxia Huang, Lei Shi 
  Abstract: This paper collects and analyses the impact of weather, air quality and point of interest data on residents’ daily travel, establishes a fusion model combined the convolutional neural network based on point of interest data and gated recurrent neural network prediction model to investigate the influence of weather and air quality on the demand of online ride-hailing, uses Pearson correlation coefficient to calculate the correlation between various external factors and ride-hailing order data. Analyse the important factors affecting ride-hailing order volume through correlation analysis. In order to improve the stability of the network, a residual module is added. The results show that the models constructed in this paper has good prediction accuracy. The study shows the incorporation of multi-source data can effectively improve the prediction accuracy of the online ride-hailing prediction model.
  Keywords: online ride-hailing demand; gated recurrent unit; GRU; convolutional neural network; CNN; travel demand.
  DOI: 10.1504/IJSPM.2024.10063423
   
  
• Lane detection method based on improved Hough transform  
  by Yimin Yang 
  Abstract: In intelligent driving, how to keep the vehicle on the road safely and accurately without deviating from the road, is an important topic. In practice, machine vision is commonly used to effectively detect lane lines, so as to alarm vehicles that deviate from lane lines. In this paper, the detection of lane lines includes image pre-processing to obtain areas of interest, histogram enhancement for low-contrast images, median filtering to remove image noise while preserving details, and Otsu threshold segmentation method to separate targets in images. After image pre-processing, the Laplacian of Gaussian operator is selected for edge detection by comparing and analysing several operators. Finally, the improved Hough transform is used to realise the lane detection within the limited parameters, reducing the computation and saving the running time. Experimental results show that the proposed algorithm can effectively detect lane lines in normal weather or under low contrast.
  Keywords: lane detect; image enhancement; edge detection; Hough transform.
  DOI: 10.1504/IJSPM.2024.10064171
   
  
• Mobile agents-based modelling for the vehicular network congestion problem resolution  
  by Soumia Mameri, Yacine Kissoum, Mohammed Redjimi 
  Abstract: Traffic management systems are technologies designed to enhance traffic flow and to decrease the congestion that often affects emergency vehicles among other cases. These technologies can be used both on in urban streets areas and on highways. This work focuses on the adaptation of intelligent agents in Vehicular Ad hoc Networks (VANET), in order to detect and prevent traffic congestion on intersections streets and to minimize the waiting time spent by vehicles in traffic lights queue especially for priority vehicles. The modeling of such systems requires tools, which hold features such as mobility and context awareness. This paper proposes a conceptual framework based on a multi-agent system for VANET decision support in dynamic smart environments. The system is modeled using a powerful paradigm called nets within nets and simulated by using real scenarios on Renew tools. A case study is presented and detailed, and the simulation results in a vehicular network show that our method can run stably in various scenarios which significantly reduces vehicle congestion and pedestrian congestion.
  Keywords: mobile agent; vehicular network; Renew tool; multiagent systems.
  DOI: 10.1504/IJSPM.2024.10064350
   
  
• Optimisation of overhead crane path based on RRT-A* fusion improvement algorithm  
  by Guangyu Mu, Mengru Zhang, Gang Wu, Zhijun Li, Lanlan Pan 
  Abstract: A novel RRT-A* fusion improvement algorithm is proposed, in this paper, to overcome limitations inherent in conventional path planning methods that overlook unique constraints related to motion direction and inertia in overhead crane operations. Initially, environmental modelling is refined by expanding and integrating obstacles to ensure crane safety during object lifting manoeuvres. Subsequently, two optimisation strategies are deployed: an extended optimisation approach to bolster the basic RRT algorithm and a direction weight optimisation strategy to fine-tune the A* algorithm. These enhancements enhance path search efficiency, addressing issues such as unreasonable diagonal path cost computation and turning point cost in A*. Finally, the combined algorithms are validated for feasibility. Results affirm the efficacy of the proposed RRT-A* algorithm in generating collision-free obstacle avoidance paths for overhead cranes, showcasing advantages in path length, turning point reduction, and energy efficiency.
  Keywords: overhead crane; path planning; RRT algorithm; A* algorithm; obstacle avoidance; collision-free path.
  DOI: 10.1504/IJSPM.2024.10064854
   
  
• Estimation of the service level in a materials analysis laboratory  
  by Josue Rojas Rodríguez, Gaston Vertiz Camaron, Jenaro Nosedal-Sanchez, José Concepción López Rivera 
  Abstract: This work introduces a materials laboratory for civil engineering where the time required to perform each test is not deterministic, likewise the overall performance of this laboratory varies over the time. The process begins by filling out an application and ends with the results report delivery. This article aims the evaluation, analysis and improvement proposes of the service level of the laboratory. First performance indicators were defined and then the simulation model was generated and implemented to estimate the resulting values of the process; next, the system’s operations were simulated, different scenarios were assessed, and the service level achieved was calculated. Considering outcomes from simulation process, the system was evaluated and analysed against the overall equipment effectiveness, thus the model provides a decision support tool to identify different configurations to achieve service level expected. Based on the obtained data, service level and key performance indicators were calculated for future scenarios.
  Keywords: key performance indicators; KPIs; simulation; work orders; materials laboratory; performance.
  DOI: 10.1504/IJSPM.2024.10064887
   
  
• Simulation-based approach for the dynamic definition of engineering processes  
  by Rodrigo Pagliares, Daniel Pereira, Celso Hirata 
  Abstract: Engineering processes are improved during project execution to better direct team activities and satisfy project goals and constraints. Simulation can be used to support the decision-making of what process changes to accomplish, but it requires knowledge and effort in modelling, implementation, and experimentation. We propose a simulation-based approach to help the dynamic definition of engineering processes. Process engineers and project managers improve process after evaluating process alternatives using simulation. The approach employs automatic translation of engineering processes to simulation models that are parametrised with up-to-date data of process performance, systematically collected. The approach also prescribes activities that allow experimenting with the generated simulation models. We developed a tool prototype and used it in a case study to demonstrate the feasibility of the approach. The results indicate that the approach is feasible and addresses the problem of what process changes to perform during enactment in order to satisfy project goals.
  Keywords: decision-making; project management; dynamic definition; process engineering; process modelling; process improvement; process enactment.
  DOI: 10.1504/IJSPM.2023.10064930