A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints

A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the pr...

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Published inInternational journal of production research Vol. 56; no. 16; pp. 5293 - 5305
Main Authors Zhang, Xiang Yi, Chen, Lu
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 18.08.2018
Taylor & Francis LLC
Subjects
Algorithms
Constraints
Crossovers
differential evolution
Evolutionary algorithms
hybrid flow shop
Integer programming
Job shop scheduling
Job shops
Linear programming
machine eligibility
Mixed integer
Production scheduling
rotor production
scheduling
Sensitivity analysis
Tightness
Online AccessGet full text
ISSN0020-7543
1366-588X
DOI10.1080/00207543.2017.1408971

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Abstract A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the problem is provided and solved by the Cplex solver. In order to solve larger sized problems, a discrete differential evolution (DDE) algorithm with a modified crossover operator is proposed. More importantly, a new decoder addressing the machine eligibility constraints is developed and embedded to the algorithm. To validate the performance of the proposed DDE algorithm, various test problems are examined. The efficiency of the proposed algorithm is compared with two other algorithms modified from the existing ones in the literatures. A one-way ANOVA analysis and a sensitivity analysis are applied to intensify the superiority of the new decoder. Tightness of due dates and different levels of scarcity of machines subject to machine eligibility restrictions are discussed in the sensitivity analysis. The results indicate the pre-eminence of the new decoder and the proposed DDE algorithm.
AbstractList A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the problem is provided and solved by the Cplex solver. In order to solve larger sized problems, a discrete differential evolution (DDE) algorithm with a modified crossover operator is proposed. More importantly, a new decoder addressing the machine eligibility constraints is developed and embedded to the algorithm. To validate the performance of the proposed DDE algorithm, various test problems are examined. The efficiency of the proposed algorithm is compared with two other algorithms modified from the existing ones in the literatures. A one-way ANOVA analysis and a sensitivity analysis are applied to intensify the superiority of the new decoder. Tightness of due dates and different levels of scarcity of machines subject to machine eligibility restrictions are discussed in the sensitivity analysis. The results indicate the pre-eminence of the new decoder and the proposed DDE algorithm.
Author Zhang, Xiang Yi
Chen, Lu
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  surname: Chen
  fullname: Chen, Lu
  email: chenlu@sjtu.edu.cn
  organization: School of Mechanical Engineering, Shanghai Jiao Tong University
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Snippet A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated...
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SubjectTerms Algorithms
Constraints
Crossovers
differential evolution
Evolutionary algorithms
hybrid flow shop
Integer programming
Job shop scheduling
Job shops
Linear programming
machine eligibility
Mixed integer
Production scheduling
rotor production
scheduling
Sensitivity analysis
Tightness
Title A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints
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