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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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.
|Research Areas:||Middlesex University Schools and Centres > School of Science and Technology > Computer and Communications Engineering|
Middlesex University Schools and Centres > School of Science and Technology > Computer Science > Artificial Intelligence group
|Permissions granted by publisher:||We acknowledge permission from IJIIP for hosting published work. (5/11)|
|Deposited On:||26 Apr 2011 16:55|
|Last Modified:||07 Jan 2015 08:04|
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