A meta-heuristic method for solving scheduling problem: crow search algorithm

被引:9
|
作者
Adhi, Antono [1 ]
Santosa, Budi [1 ]
Siswanto, Nurhadi [1 ]
机构
[1] Inst Teknol Sepuluh Nopember, Dept Ind Engn, Kampus ITS, Sukolilo Surabaya 60111, Indonesia
来源
INTERNATIONAL CONFERENCE ON INDUSTRIAL AND SYSTEMS ENGINEERING (ICONISE) 2017 | 2018年 / 337卷
关键词
PARTICLE SWARM OPTIMIZATION; LOCAL SEARCH; SHOP;
D O I
10.1088/1757-899X/337/1/012003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.
引用
收藏
页数:6
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