Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

被引:0
作者
Heow Pueh Lee [1 ]
机构
[1] Institute of High Performance Computing,Singapore 117528,Singapore
关键词
job shop scheduling problem; clonal selection algorithm; simulated annealing; global search; local search;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper.In the proposed algorithm,the clonal selection and the local search mechanism are designed to enhance exploration and exploitation.In the clonal selection mechanism,clonal selection,hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration.In the local search mechanism,a simulated annealing local search algorithm based on Nowicki and Smutnicki’s neighborhood is presented to exploit local optima.The proposed algorithm is examined using some well-known benchmark problems.Numerical results validate the effectiveness of the proposed algo-rithm.
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页码:111 / 119
页数:9
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