Bi-criteria ant colony optimization algorithm for minimizing makespan and energy consumption on parallel batch machines

Document Type

Article

Publication Date

6-1-2017

Abstract

We investigate the problem of minimizing the makespan and the total electric power cost simultaneously on a set of parallel identical batch-processing machines, where the jobs with non-identical sizes dynamically arrive. To address the bi-criteria problem, a Pareto-based ant colony optimization (PACO) algorithm is proposed. Depending on whether the current batch being delayed after the job is added into, two candidate lists are constructed to narrow the search space. Moreover, heuristic information is designed for each candidate list to guide the search. In addition, the objective-oriented local optimization methods are applied to improve the solution quality. Finally, the proposed algorithm is compared with existing multi-objective algorithms through extensive simulation experiments. The experimental results indicate that the proposed algorithm outperforms all of the compared algorithms, especially for large-scale problems.

Identifier

85013498312 (Scopus)

Publication Title

Applied Soft Computing Journal

External Full Text Location

https://doi.org/10.1016/j.asoc.2017.01.044

ISSN

15684946

First Page

226

Last Page

237

Volume

55

Grant

ADXXBZ201509

Fund Ref

National Natural Science Foundation of China

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