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首页> 外文期刊>Applied Mathematical Modelling >Development of a comprehensive model and BFO algorithm for a dynamic cellular manufacturing system
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Development of a comprehensive model and BFO algorithm for a dynamic cellular manufacturing system

机译：动态蜂窝制造系统综合模型和BFO算法的开发

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A comprehensive multiobjective model of the cellular manufacturing system (CMS) operating in a dynamic environment is developed. The proposed algorithm takes into consideration various important cell design issues, such as machine assignment, intercell/intracell material handling, worker assignment, outsourcing and workload balancing based on operational time and operation sequence of the parts. Workload balancing among cells tends to increase CMS processing costs, and hence the use of multiobjective optimization methods is required for CMS solutions that are optimal and feasible. A multiobjective matrix-based bacteria foraging optimization algorithm with traced constraint handling (MOMBATCH) is developed for this purpose. The performance of the proposed algorithm is compared with that of the non-dominated sorting genetic algorithm 11 method that is frequently reported in the literature and the off-the-shelf program CPLEX. The results show that MOMBATCH solves problems more efficiently in terms of finding optimal solutions while maintaining the Pareto frontier diversity.
机译：开发了在动态环境中运行的蜂窝制造系统（CMS）的综合多目标模型。所提出的算法考虑了各种重要的单元设计问题，例如机器分配，单元间/单元内物料搬运，工人分配，外包以及基于零件的操作时间和操作顺序的工作量平衡。单元之间的工作负载平衡往往会增加CMS的处理成本，因此，对于最优且可行的CMS解决方案，需要使用多目标优化方法。为此，开发了一种基于多目标矩阵的具有跟踪约束处理的细菌觅食优化算法（MOMBATCH）。将所提算法的性能与文献中经常报道的非支配排序遗传算法11方法和现成程序CPLEX的性能进行比较。结果表明，MOMBATCH在寻找最佳解决方案的同时更有效地解决了问题，同时保持了Pareto边界的多样性。

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