Cat swarm optimization to solve job shop scheduling problem

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.