A multi-swarm fruit fly optimization algorithm to minimize makespan for the hybrid flowshop problem

This paper aims to minimize makespan for the hybrid flowshop scheduling problem. We present a novel Fruit Fly Optimization (FFO), called multi-swarm FFO, by introducing a multiple-swarm strategy and a competition-and-updating mechanism to the basic FFO. The parameters and operators for the presented...

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Vydáno v:Chinese Control Conference s. 2796 - 2800
Hlavní autoři: Duan, Junhua, Chen, Qingda, Sun, Weiqing, Pan, Quanke
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Technical Committee on Control Theory, CAA 01.07.2017
Témata:
Artificial intelligence
Economic indicators
Evolutionary Algorithm
Fruit Fly Optimization
Hafnium
Hybrid Flowshop
Job shop scheduling
Makespan
Optimization
Sociology
Statistics
ISSN:1934-1768
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Shrnutí:This paper aims to minimize makespan for the hybrid flowshop scheduling problem. We present a novel Fruit Fly Optimization (FFO), called multi-swarm FFO, by introducing a multiple-swarm strategy and a competition-and-updating mechanism to the basic FFO. The parameters and operators for the presented MMFO algorithm are calibrated by means of a design of experiments approach. The numerical comparisons show that MFFO performs much better than several well-known metaheuristics in the literature for the considered HFS problem.
ISSN:1934-1768
DOI:10.23919/ChiCC.2017.8027788