A meta-heuristic for minimizing total weighted flow time on parallel batch machines

Document Type

Article

Publication Date

11-1-2018

Abstract

To address the problem of minimizing the total weighted completion time on parallel batch processing machines with identical machine capacities, non-identical job sizes and unequal weights, an effective meta-heuristic based on ant colony optimization is proposed. After presenting a mathematic model of the problem, we provide an algorithm to calculate the lower bound. Then, a meta-heuristic is proposed to solve the problem. The heuristic information is defined with consideration of job weights and job sizes. Meanwhile, a candidate set for constructing the solution is used to narrow the search space. Additionally, to improve the solution quality, a local optimization strategy is incorporated. Simulation results show that the proposed algorithm is able to obtain a high-quality solution within a reasonable time, and outperforms the compared algorithms.

Identifier

85052949429 (Scopus)

Publication Title

Computers and Industrial Engineering

External Full Text Location

https://doi.org/10.1016/j.cie.2018.08.009

ISSN

03608352

First Page

298

Last Page

308

Volume

125

Grant

71601001

Fund Ref

National Natural Science Foundation of China

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