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首页> 外文期刊>International Journal of Innovative Computing Information and Control >A HYBRID OF BIO-INSPIRED AND MUSICAL-HARMONY APPROACH FOR MACHINE LOADING OPTIMIZATION IN FLEXIBLE MANUFACTURING SYSTEM
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A HYBRID OF BIO-INSPIRED AND MUSICAL-HARMONY APPROACH FOR MACHINE LOADING OPTIMIZATION IN FLEXIBLE MANUFACTURING SYSTEM

机译：柔性制造系统中机械负载优化的生物启发与音乐和谐混合算法

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摘要

Manufacturing industries are facing fierce challenges in handling product competitiveness, shorter product cycle time and product varieties. The situation demands a need to improve the effectiveness and efficiency of capacity planning and resource optimization while still maintaining their flexibilities. Machine loading - one of the important components of capacity planning is known for its complexity that encompasses various types of flexibilities pertaining to part selection, machine and operation assignment along with constraints. Various studies are done to balance the productivity and flexibility in flexible manufacturing system (FMS). From the literature, researchers have developed many approaches to reach a suitable balance of exploration (global improvement) and exploitation (local improvement). We adopt a hybrid of population approaches; hybrid constraint-chromosome genetic algorithm and harmony search algorithm (H-CCGaHs), to solve this problem that aims at mapping a feasible solution to the domain problem. The objectives are to minimize the system unbalance as well as to increase the throughput while satisfying the constraints such as machine time availability and tool slots. The proposed algorithm is tested for its performance on 10 sample problems available in FMS literature and compared with existing solution approaches.
机译：制造业在处理产品竞争力，缩短产品周期时间和产品种类方面面临着严峻的挑战。这种情况需要在保持灵活性的同时提高容量规划和资源优化的有效性和效率。机器装载-能力计划的重要组成部分之一以其复杂性而闻名，它包括与零件选择，机器和操作分配以及约束有关的各种类型的灵活性。为了平衡柔性制造系统（FMS）的生产率和灵活性，进行了各种研究。从文献中，研究人员已经开发出许多方法来达到勘探（全球改善）和开发（局部改善）之间的适当平衡。我们采用混合人口方法；混合约束染色体遗传算法和和谐搜索算法（H-CCGaHs），以解决该问题，旨在为域问题映射一个可行的解决方案。目的是在满足诸如机器时间可用性和工具插槽之类的约束的同时，最大程度地减少系统不平衡并提高吞吐量。该算法针对FMS文献中存在的10个样本问题的性能进行了测试，并与现有的解决方案进行了比较。

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