Single Objective Evolutionary Algorithm for Job Shop Scheduling Problem
Journal Title: INTERNATIONAL JOURNAL OF MATHEMATICS TRENDS AND TECHNOLOGY - Year 2012, Vol 3, Issue 1
Abstract
— Job shop scheduling belongs to the class of NPhard problems. There are a number of algorithms in literature for finding near optimal solution for the job shop scheduling problem. Many of these algorithms exploit the problem specific information and hence are less general. However, single objective evolutionary algorithms for job shop scheduling are general and produce better results. In this paper, we discuss approaches to developing single objective evolutionary algorithm for solving the job shop scheduling problem. Initial population is generated randomly. Two-row chromosome structure is adopted based on working procedure and machine distribution. The relevant crossover and mutation operation is also designed. It jumped from the local optimal solution, and the search area of solution is improved. Finally, the algorithm is tested on instances of 8 working procedure and 5 machines. The result shows that the evolutionary algorithm has been successfully applied to the job shop scheduling problems efficiency
Authors and Affiliations
G. Uma Sankar1 , Dr. D. Saravanan
Keywords
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