Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

2nd International Manufacturing Engineering Conference; 3rd Asia-Pacific Conference on Manufacturing Systems

Anuar, Nurul Izah^1 ; Saptari, Adi^2

Centre for Diploma Programmes, Multimedia University, Jalan Ayer Keroh Lama, Ayer Keroh, Melaka

75450, Malaysia^1

Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka

76100, Malaysia^2

关键词: Bench-mark problems;    Complex scheduling;    Job shop manufacturing;    Job shop scheduling problems;    Objective functions;    Performance evaluations;    Scheduling problem;    Stochastic optimization techniques;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/114/1/012055/pdf
DOI  :  10.1088/1757-899X/114/1/012055

来源: IOP

【 摘 要 】

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.