Application of Adaptive Particle Swarm Optimization to Bi-level Job-Shop Scheduling Problem

Title & Authors
Application of Adaptive Particle Swarm Optimization to Bi-level Job-Shop Scheduling Problem
Kasemset, Chompoonoot;

Abstract
This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is $\small{10{\}$$\small{times}10}$ JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.
Keywords
Adaptive Particle Swarm Optimization;Job-Shop Scheduling;Bi-level Programming;
Language
English
Cited by
1.
Schedulability Analysis for Noncyclic Operation of Time-Constrained Cluster Tools With Time Variation, IEEE Transactions on Automation Science and Engineering, 2016, 13, 3, 1409
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