Solving job shop scheduling problem using genetic algorithm with penalty function

Sun, Liang and Cheng, Xiaochun and Liang, Yanchun (2010) Solving job shop scheduling problem using genetic algorithm with penalty function. International Journal of Intelligent Information Processing, 1 (2). pp. 65-77. ISSN 2093-1964

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Abstract

This paper presents a genetic algorithm with a penalty function for the job shop scheduling problem. In the context of proposed algorithm, a clonal selection based hyper mutation and a life span extended strategy is designed. During the search process, an adaptive penalty function is designed so that the algorithm can search in both feasible and infeasible regions of the solution space. Simulated experiments were conducted on 23 benchmark instances taken from the OR-library. The results show the effectiveness of the proposed algorithm.

Item Type:Article
Research Areas:School of Science and Technology > Science & Technology
ID Code:7772
Permissions granted by publisher:We acknowledge permission from IJIIP for hosting published work. (5/11)
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Deposited On:26 Apr 2011 16:55
Last Modified:19 Jul 2014 04:26

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