A Hybrid Ant Colony Optimization to Minimize the Total Completion Time on a Single Batch Processing Machine with Non-identical Job Sizes

被引：0

作者：

Xu, Rui ^{[1
]}

Chen, Hua-Ping ^{[1
]}

Zhu, Jun-Hong ^{[2
]}

Shao, Hao ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Informat Management & Decis Sci, Hefei 230026, Anhui, Peoples R China

[2] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 7, PROCEEDINGS | 2008年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/ICNC.2008.384

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper aims at minimizing the total completion time for a single batch processing machine with non-identical job sizes. For this problem, each job has a corresponding processing time and size. The machine can process the jobs in batches as long as the total size of all the jobs in a batch does not exceed the machine capacity. The processing time of a batch is equal to the longest processing time among all the jobs in that batch. This problem is NP-hard and hence a Chaotic Ant Colony Optimization algorithm based on Batch sequence (BCACO) is proposed. Random instances were used to test the effectiveness of the proposed approach. Computational results show that BCACO significantly outperforms other algorithms addressed in the literature.

引用

页码：439 / +

页数：2

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