Performance Evaluation Of Different Types Of Particle Representation Procedures Of Particle Swarm Optimization In Job-Shop Scheduling Problems

Nurul Izah, Anuar and Adi, Saptari (2016) Performance Evaluation Of Different Types Of Particle Representation Procedures Of Particle Swarm Optimization In Job-Shop Scheduling Problems. IOP Conference Series: Materials Science And Engineering, 114 (1). pp. 1-5. ISSN 1757-8981

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Official URL: http://iopscience.iop.org/article/10.1088/1757-899...

Abstract

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Technology Management and Technopreneurship
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	29 Sep 2016 00:05
Last Modified:	12 Sep 2021 16:17
URI:	http://eprints.utem.edu.my/id/eprint/17261
Statistic Details:	View Download Statistic

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