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An Artificial Bee Colony Algorithm for the Distributed Hybrid Flowshop Scheduling Problem

机译:一种用于分布式混合流程调度问题的人工蜂殖民地算法

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The distributed hybrid flowshop scheduling problem (DHFSP) is derived from the hybrid flowshop scheduling problem (HFSP), which involves two scheduling assignment decisions-assignment of jobs to factories and scheduling jobs in each factory. DHFSP is encountered in many practical industry applications recently. The standard DHFSP has never been discussed in any previous literature, and it is addressed first addressed in this work. In this paper, the mixed-integer linear programming (MILP) model is proposed. An improved discrete artificial bee colony (DABC) algorithm for minimizing makespan is proposed as well. Novel encoding and decoding methods are developed for DHFSP. The constructive heuristic, an improved NEH heuristic, is employed to build high quality and diversified solutions for the initial population. Two neighborhood search methods based on swap and insertion neighborhood structures are proposed for DHFSP. Comprehensive computational comparisons and statistical analysis demonstrate the effectiveness of the proposed DABC algorithm when compared with a genetic algorithm (GA) and an iterated greedy (IG) algorithm.
机译:分布式混合流程调度问题(DHFSP)来自混合流程调度问题(HFSP),它涉及两个调度分配决策 - 将作业分配给每个工厂中的工厂和调度作业。最近在许多实用行业应用中遇到了DHFSP。标准的DHFSP从未在任何以前的文献中讨论过,并在这项工作中首次解决了它。在本文中,提出了混合整数线性编程(MILP)模型。提出了一种改进的离散人工蜂菌落(DABC)用于最小化MEPESPHAN的算法。为DHFSP开发了新颖的编码和解码方法。建设性启发式,改进的尼赫启发式,用于为初始人口构建高质量和多样化的解决方案。为DHFSP提出了基于交换和插入邻域结构的两个邻域搜索方法。综合计算比较和统计分析证明了与遗传算法(GA)和迭代贪婪(IG)算法进行比较时所提出的DABC算法的有效性。

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