Cat swarm optimization to solve job shop scheduling problem

A. Bouzidi, M. E. Riffi
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引用次数: 27

Abstract

The Job shop scheduling problem is known as a combinatorial optimization problem that aims to find best sequence of operations with optimal execution time called makespan. Various algorithms are used to resolve it. This research paper aims to provide a new adaptation to solve the job shop scheduling problem. Discrete cat swarm optimization algorithm (CSO) consists of two modes, which are: the seeking mode when the cat is resting and the tracing mode when the cat is hunting. These two modes are combined by a mixture ratio. The result applied to some benchmark instances and proves thus the performance of this adaptation.
Cat群算法求解作业车间调度问题
作业车间调度问题被称为组合优化问题,其目的是找到具有最佳执行时间(称为makespan)的最佳操作序列。各种算法被用来解决它。本研究旨在提供一种新的方法来解决作业车间调度问题。离散猫群优化算法(CSO)包括两种模式,即猫休息时的搜索模式和猫狩猎时的跟踪模式。这两种模式通过混合比组合在一起。将结果应用于一些基准实例,从而证明了这种自适应的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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