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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Vydané v:Chinese Control Conference s. 2796 - 2800
Hlavní autori: Duan, Junhua, Chen, Qingda, Sun, Weiqing, Pan, Quanke
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Technical Committee on Control Theory, CAA 01.07.2017
Predmet:
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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Abstract 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.
AbstractList 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.
Author Pan, Quanke
Duan, Junhua
Sun, Weiqing
Chen, Qingda
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  surname: Duan
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  organization: Computation Center, Shanghai University, Shanghai, 200444, China
– sequence: 2
  givenname: Qingda
  surname: Chen
  fullname: Chen, Qingda
  email: cqd0309@126.com
  organization: State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang, 110819, China
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  givenname: Weiqing
  surname: Sun
  fullname: Sun, Weiqing
  email: Sunweiqing@shu.edu.cn
  organization: Computation Center, Shanghai University, Shanghai, 200444, China
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  givenname: Quanke
  surname: Pan
  fullname: Pan, Quanke
  email: panquanke@shu.edu.cn
  organization: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China
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Snippet 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...
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SubjectTerms Artificial intelligence
Economic indicators
Evolutionary Algorithm
Fruit Fly Optimization
Hafnium
Hybrid Flowshop
Job shop scheduling
Makespan
Optimization
Sociology
Statistics
Title A multi-swarm fruit fly optimization algorithm to minimize makespan for the hybrid flowshop problem
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