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首页> 外文期刊>International Journal of Industrial Engineering Computations >Single machine batch processing problem with release dates to minimize total completion time
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Single machine batch processing problem with release dates to minimize total completion time

机译:具有发布日期的单机批处理问题,以最大程度地减少总完成时间

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A single machine batch processing problem with release dates to minimize the total completion time (1|rj,batch|Σ Cj ) is investigated in this research. An original mixed integer linear programming (MILP) model is proposed to optimally solve the problem. Since the research problem at hand is shown to be NP-hard, several different meta-heuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) are used to solve the problem. To find the most performing heuristic optimization technique, a set of test cases ranging in size (small, medium, and large) are randomly generated and solved by the proposed meta-heuristic algorithms. An extended comparison analysis is carried out and the outperformance of a hybrid meta-heuristic technique properly combining PSO and genetic algorithm (PSO-GA) is statistically demonstrated.
机译:在这项研究中,研究了具有发布日期的单机批处理问题,该问题可以最大程度地减少总完成时间(1 | rj,batch |ΣCj)。提出了一种原始的混合整数线性规划(MILP)模型来最佳地解决该问题。由于当前的研究问题显示为NP难题,因此使用了基于禁忌搜索(TS)和粒子群优化(PSO)的几种不同的元启发式算法来解决该问题。为了找到性能最高的启发式优化技术,将随机产生一组大小(大小,大小不等)的测试用例,并通过提出的元启发式算法进行求解。进行了扩展的比较分析,并统计地证明了将PSO和遗传算法(PSO-GA)正确组合的混合元启发式技术的出色表现。

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