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

Author

Xu, Rui ; Chen, Hua-Ping ; Zhu, Jun-Hong ; Shao, Hao

Author_Institution

Dept. of Inf. Manage. & Decision Sci., Univ. of Sci. & Technol. of China, Hefei

Volume

7

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

439

Lastpage

443

Abstract

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.

Keywords

batch processing (industrial); optimisation; NP-hard problem; batch processing machine; batch sequence; chaotic ant colony optimization; hybrid ant colony optimization; machine capacity; nonidentical job sizes; Ant colony optimization; Chaos; Conference management; Heuristic algorithms; Information management; Job shop scheduling; Optimal scheduling; Semiconductor device manufacture; Technology management; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2008. ICNC '08. Fourth International Conference on

Conference_Location

Jinan

Print_ISBN

978-0-7695-3304-9

Type

conf

DOI

10.1109/ICNC.2008.384

Filename

4668016