An ACO algorithm for makespan minimization in parallel batch machines with non-identical job sizes and incompatible job families

Document Type

Article

Publication Date

1-1-2016

Abstract

We study the problem of scheduling a set of N jobs with non-identical job sizes from F different families on a set of M parallel batch machines; the objective is to minimize the makespan. The problem is known to be NP-hard. A meta-heuristic based on Max-Min Ant System (MMAS) is presented. The performance of the algorithm is compared with several previously studied algorithms by computational experiments. According to our results, the average distance between the solutions found by our proposed algorithm and the lower bounds is about 4% less than that of the best of all the compared algorithms, demonstrating that our algorithm outperforms the previously studied algorithms.

Identifier

84946606270 (Scopus)

Publication Title

Applied Soft Computing Journal

External Full Text Location

https://doi.org/10.1016/j.asoc.2015.09.056

ISSN

15684946

First Page

395

Last Page

404

Volume

38

Grant

33050044

Fund Ref

National Natural Science Foundation of China

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