DocumentCode
3160175
Title
Two-agent scheduling on a single batch processing machine with non-identical job sizes
Author
Tan, Qi ; Chen, Hua-Ping ; Du, Bing ; Li, Xiao-lin
Author_Institution
Sch. of Comput., Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
fYear
2011
fDate
8-10 Aug. 2011
Firstpage
7431
Lastpage
7435
Abstract
A new scheduling model in which both two-agent and a batch processing machine with non-identical job sizes exist is considered in this paper. Two agents compete to process their respective job sets on a common single batch processing machine. The objectives of the two agents are both to minimize the makespan. It is proved in the literature[7] that the complexity of minimizing makespan of one agent on a single batch processing machine with non-identical job sizes is NP-hard in the strong sense. We developed an improved ant colony optimal algorithm to search for the Pareto optimal solutions. The experimental results showed that the proposed algorithm could get better non-dominated solutions compared with the non-dominated sorting genetic algorithm (NSGA-II) which was widely used in solving the multi-objective optimization problem.
Keywords
Pareto optimisation; batch processing (industrial); computational complexity; job shop scheduling; minimisation; search problems; NP-hard problem; Pareto optimal solutions; ant colony optimal algorithm; batch processing machine; nonidentical job sizes; two-agent scheduling model; Batch production systems; Job shop scheduling; Measurement; Pareto optimization; Processor scheduling; batch-processing machine; makespan; non-identical job sizes; scheduling; two-agent;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location
Deng Leng
Print_ISBN
978-1-4577-0535-9
Type
conf
DOI
10.1109/AIMSEC.2011.6009883
Filename
6009883
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