research-article

Minimizing makespan for solving the distributed no-wait flowshop scheduling problem

Authors:

Kuo-Ching YingAuthors Info & Claims

Computers and Industrial Engineering, Volume 99, Issue C

Pages 202 - 209

https://doi.org/10.1016/j.cie.2016.07.027

Published: 01 September 2016 Publication History

Abstract

This paper is the first research to solve the distributed no-wait flowshop scheduling problem.The proposed ICG algorithm provides a practical means of solving this problem.This study contributes significantly to expand the research on distributed scheduling problems. This paper presents the distributed no-wait flowshop scheduling problem (DNFSP), which is the first attempt in the literature to solve this key problem faced by the manufacturing industry. A mixed integer programming (MIP) mathematical model and an iterated cocktail greedy (ICG) algorithm are developed for solving this problem of how to minimize the makespan among multiple plants. The ICG algorithm presented herein is an enhanced version of the iterated greedy algorithm, and it includes two self-tuning mechanisms and a cocktail destruction mechanism. Exhaustive computational experiments and statistical analyses show that the proposed ICG algorithm is a highly efficient approach that provides a practical means for solving the challenging DNFSP.

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Cited By

Mraihi TDriss OEL-Haouzi H(2024)Distributed Permutation Flow Shop Scheduling Problem with Worker flexibilityExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121947238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121947
Li ZBai LQian BChen Y(2024)Active learning based hyper-heuristic for the integration of production and TransportationComputers and Industrial Engineering10.1016/j.cie.2024.110381194:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.110381
Lei DDu HTang H(2023)An imperialist competitive algorithm for distributed assembly flowshop scheduling with Pm → 1 layout and transportationJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22392945:1(269-284)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-223929
Show More Cited By

Minimizing makespan for solving the distributed no-wait flowshop scheduling problem
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
    2. Online algorithms
      1. Online learning algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning

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cover image Computers and Industrial Engineering

Computers and Industrial Engineering Volume 99, Issue C

September 2016

518 pages

ISSN:0360-8352

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 September 2016

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Cited By

Mraihi TDriss OEL-Haouzi H(2024)Distributed Permutation Flow Shop Scheduling Problem with Worker flexibilityExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121947238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121947
Li ZBai LQian BChen Y(2024)Active learning based hyper-heuristic for the integration of production and TransportationComputers and Industrial Engineering10.1016/j.cie.2024.110381194:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.110381
Lei DDu HTang H(2023)An imperialist competitive algorithm for distributed assembly flowshop scheduling with Pm → 1 layout and transportationJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22392945:1(269-284)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-223929
Xu WWang LLiu DTang HLi Y(2023)Solving distributed low carbon scheduling problem for large complex equipment manufacturing using an improved hybrid artificial bee colony algorithmJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22343545:1(147-175)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-223435
Zhao FZhou GXu TZhu NJonrinaldi (2023)A knowledge-driven cooperative scatter search algorithm with reinforcement learning for the distributed blocking flow shop scheduling problemExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.120571230:COnline publication date: 15-Nov-2023
https://dl.acm.org/doi/10.1016/j.eswa.2023.120571
Avci M(2023)An effective iterated local search algorithm for the distributed no-wait flowshop scheduling problemEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.105921120:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.105921
Zhao FBao HWang LXu TZhu NJonrinaldi (2023)A heuristic and meta-heuristic based on problem-specific knowledge for distributed blocking flow-shop scheduling problem with sequence-dependent setup timesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105443116:COnline publication date: 20-Jan-2023
https://dl.acm.org/doi/10.1016/j.engappai.2022.105443
Yu YZhang FHuang J(2023)Acceleration-based artificial bee colony optimizer for a distributed permutation flowshop scheduling problem with sequence-dependent setup timesApplied Soft Computing10.1016/j.asoc.2023.110029135:COnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.asoc.2023.110029
Avci MAvci MHamzadayı A(2022)A branch-and-cut approach for the distributed no-wait flowshop scheduling problemComputers and Operations Research10.1016/j.cor.2022.106009148:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.cor.2022.106009
Karabulut KKizilay DTasgetiren MGao LKandiller L(2022)An evolution strategy approach for the distributed blocking flowshop scheduling problemComputers and Industrial Engineering10.1016/j.cie.2021.107832163:COnline publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.cie.2021.107832
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