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A Discrete Artificial Bee Colony Algorithm for Permutation Flow Shop Scheduling

Authors: Ying Liu; Dantong Ouyang; Wenxiang Gu; Lei Wang;

A Discrete Artificial Bee Colony Algorithm for Permutation Flow Shop Scheduling

Abstract

A discrete artificial bee colony algorithm (DABC) is proposed for solving the permutation flow shop scheduling problem (PFSSP) with minimum makespan criterion. Firstly, the NEH heuristic was combined the random initialization to the population for quality and diversity. Secondly, a new individual enhancement scheme is proposed to combine the swap, insert, inverse and adjacent exchange operation. Third, the fast local search is used to enhancing the individuals. Fourth, the pair-wise based local search is used to enhance the global optimal solution and escape from local minimum. Lastly, simulations and comparisons based on PFSSP benchmarks are carried out, which show that our algorithm is effectively and efficiently for solving the PFSSP.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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