A job shop scheduling Algorithm Using Big Bang-Big Crunch Strategy

被引:0
|
作者
Kang, Yan [1 ]
Li, Hao [2 ]
Wang, Chunhui [1 ]
Dai, Li [1 ]
机构
[1] Yunnan Univ, Sch Software, Dept Software Engn, Kunming, Yunnan, Peoples R China
[2] Yunnan Univ, Sch Software, Dept Network Engn, Kunming, Yunnan, Peoples R China
来源
PROCEEDINGS OF 2016 12TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2016年
关键词
!text type='JS']JS[!/text]P; Big Bang-Big Crunch Algorithm; Scheduling Problem; Neighborhood;
D O I
10.1109/CIS.2016.99
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Big Bang-Big Crunch Algorithm (BBBC) is a theoretical framework of analyzing a set of alternatives to reach the best outcome. An algorithm of Hybrid BBBC with the objective to minimize the makespan is presented to tackle the job-shop scheduling problem. The initial solutions to the typical NP-hard problem are generated according to different heuristic strategies in a combination way. Modified BB strategy is proposed by treating the obtained operations to generate the center of mass. And then all the operations are ordered by the positions of the operations obtained in BC phase. To enhance the exploitation ability, a local search strategy is proposed on basis of critical path to moving the operation sequence toward the promising solution. Finally, a set of benchmark instances is applied to test the performances of the HBBBC and to compare it with some existing methods. The results demonstrate that the proposed HBBBC algorithm is competitive and can be rapidly guided.
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页码:411 / 414
页数:4
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