基于起始时间的粒子群优化生产调度方法

J. Grobler, A. Engelbrecht, J. Joubert, S. Kok
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引用次数: 5

摘要

本文为南非一家专门从事供应链优化的公司Optimatix的复杂调度问题提供了一个通用公式。为了解决所提问题的复杂要求,在经典作业车间调度问题中加入了各种附加约束。这些包括生产停机时间、计划维护、机器故障、与顺序相关的安装时间、发布日期和每个作业的多个前任。在主要资源(机器)和辅助资源(劳动力、工具和夹具)之间也实现了区分。此外,本文还将粒子群优化(PSO)技术应用于该问题的求解。粒子群优化是一种基于随机种群的优化技术,起源于对鸟类和鱼类社会行为的研究。除了论文的意义在于提出的问题之前没有得到解决,改进生产计划的好处可以概括为包括降低成本,客户满意度,提高盈利能力和整体竞争优势
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A starting-time-based approach to production scheduling with Particle Swarm Optimization
This paper provides a generic formulation for the complex scheduling problems of Optimatix, a South African company specializing in supply chain optimization. To address the complex requirements of the proposed problem, various additional constraints were added to the classical job shop scheduling problem. These include production downtime, scheduled maintenance, machine breakdowns, sequence-dependent set-up times, release dates and multiple predecessors per job. Differentiation between primary resources (machines) and auxiliary resources (labour, tools and jigs) were also achieved. Furthermore, this paper applies particle swarm optimization (PSO), a stochastic population based optimization technique originating from the study of social behavior of birds and fish, to the proposed problem. Apart from the significance of the paper in that the proposed problem has not been addressed before, the benefit of an improved production schedule can be generalized to include cost reduction, customer satisfaction, improved profitability and overall competitive advantage
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