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An evolutionary approach to the job-shop scheduling problem

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2 Author(s)
G. H. Kim ; Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA ; C. S. G. Lee

This paper focuses on the heuristic hybridization and the genetic search as a methodology to develop a computationally efficient heuristic for the job-shop scheduling problem (JSP). In order to adapt the JSP to a genetic algorithm (GA), the ASGPL (Active-Schedule Generation with a Priority-List) algorithm with a hopping scheme was proposed, and using a GA, an iterative schedule improvement procedure called EVIS (Evolutionary Intracell Scheduler) was designed. The genetic search in EVIS was parallelized with a model of subpopulations and migration. Without implementing any problem-tailored heuristic for the job-shop scheduling problem, EVIS was able to find optimal solutions to a number of different problem instances in reasonable computation time

Published in:

Robotics and Automation, 1994. Proceedings., 1994 IEEE International Conference on

Date of Conference:

8-13 May 1994