Forthcoming Articles

International Journal of Computing Science and Mathematics

International Journal of Computing Science and Mathematics (IJCSM)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Computing Science and Mathematics (2 papers in press)

Regular Issues

  • Multi-Stage Adaptive Firefly Algorithm with Enhanced Search   Order a copy of this article
    by Kefeng Li, Na Jin, Tang Jun, Cao Yiqing 
    Abstract: As a popular swarm intelligence optimization approach, firefly algorithm (FA) has exhibited excellent search capabilities in various optimization problems. However, FA still has some limitations. The search efficiency is sensitive to the step size factor, and the single search pattern results in slow convergence rate. To tackle these issues, this paper proposes a multi-stage adaptive FA with enhanced search (namely MSAFAES). First, a new adaptive parameter method is designed, in which the entire search is divided into two stages. Different parameters strategies are adopted for different search stages. Then, three types of search patterns are employed in the search process. To validate the performance of MSAFAES, ten well-known benchmark problems are tested. Computational results demonstrate the effectiveness of MSAFAES when compared with three other FA variants.
    Keywords: Firefly algorithm; multi-stage; adaptive; multi-strategy; optimization.
    DOI: 10.1504/IJCSM.2025.10075779
     
  • Multi-Objective Hierarchical Model for Coupled Intelligent Optimisation of Master Production Planning and Material Management and its Optimisation Research   Order a copy of this article
    by Yong Jin, Yanghua Gao, Fanghua Ning, Yutao Jin 
    Abstract: To address the insufficient integration between master production scheduling (MPS) and material management (MM) in Chinas tobacco industry, this study proposes a multi-objective hierarchical model for their collaborative optimisation. The model features a two-layer structure: the upper level optimises capacity utilisation and production costs, while the lower level minimises material waste and inventory levels. The NSGA-II algorithm was adopted to solve the model, and its effectiveness was verified through a case study based on actual enterprise operational data. Results demonstrate that the model significantly reduces raw-material waste by 19.3%, shortens the production cycle by 14 days, and improves Pareto-frontier efficiency by 32.7%. The study validates the models effectiveness in complex, long-cycle production scenarios, offering a practical solution for refined production management in the tobacco industry.
    Keywords: cigarette; master production planning; material management; multi-objective optimisation; genetic algorithm; progressive model.
    DOI: 10.1504/IJCSM.2025.10076101
     

 

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