Skipping Strategy (SS) for Initial Population of Job-Shop Scheduling Problem

被引：0

作者：

Abdolrazzagh-Nezhad, M. ^{[1
]}

Nababan, E. B. ^{[2
]}

Sarim, H. M. ^{[3
]}

机构：

[1] Bozorgmehr Univ Qaenat, Fac Engn, Dept Comp Engn, Qaen, Iran

[2] Univ Sumatera Utara, Fac Comp Sci & Informat Technol, Dept Informat Technol, Medan, Indonesia

[3] Univ Kebangsaan Malaysia, Ctr Artificial Intelligence Technol, Data Min & Optimizat Res Grp, Ukm Bangi 43600, Selangor, Malaysia

来源：

2ND INTERNATIONAL CONFERENCE ON COMPUTING AND APPLIED INFORMATICS 2017 | 2018年 / 978卷

关键词：

ALGORITHM; OPTIMIZATION;

D O I：

10.1088/1742-6596/978/1/012054

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Initial population in job-shop scheduling problem (JSSP) is an essential step to obtain near optimal solution. Techniques used to solve JSSP are computationally demanding Skipping strategy (SS) is employed to acquire initial population after sequence of job on machine and sequence of operations (expressed in Plates jobs and mPlates-jobs) are determined. The proposed technique is applied to benchmark datasets and the results are compared to that of other initialization techniques. It is shown that the initial population obtained from the SS approach could generate optimal solution.

引用

页数：7

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