Hybrid Flow-Shop: a Memetic Algorithm Using Constraint-Based Scheduling for Efficient Search

The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the mem...

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Vydáno v:Journal of mathematical modelling and algorithms Ročník 8; číslo 3; s. 271 - 292
Hlavní autoři: Jouglet, Antoine, Oğuz, Ceyda, Sevaux, Marc
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 01.08.2009
Springer Nature B.V
Springer Verlag
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ISSN:1570-1166, 2214-2487, 1572-9214, 2214-2495
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Abstract The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as the local search engine of the memetic algorithm. Next, we present the new memetic algorithm. We lastly explain the computational experiments carried out to evaluate the performance of three algorithms (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm) in terms of both the quality of the solutions produced and the efficiency. These results demonstrate that the memetic algorithm produces better quality solutions and that it is very efficient.
AbstractList The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as the local search engine of the memetic algorithm. Next, we present the new memetic algorithm. We lastly explain the computational experiments carried out to evaluate the performance of three algorithms (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm) in terms of both the quality of the solutions produced and the efficiency. These results demonstrate that the memetic algorithm produces better quality solutions and that it is very efficient.
The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as the local search engine of the memetic algorithm. Next, we present the new memetic algorithm. We lastly explain the computational experiments carried out to evaluate the performance of three algorithms (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm) in terms of both the quality of the solutions produced and the efficiency. These results demonstrate that the memetic algorithm produces better quality solutions and that it is very efficient. [PUBLICATION ABSTRACT]
Author Sevaux, Marc
Oğuz, Ceyda
Jouglet, Antoine
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  givenname: Ceyda
  surname: Oğuz
  fullname: Oğuz, Ceyda
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  givenname: Marc
  surname: Sevaux
  fullname: Sevaux, Marc
  organization: UEB—Lab-STICC, UMR CNRS 3192, Centre de Recherche, Université de Bretagne Sud
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Keywords Multiprocessor task scheduling
Memetic algorithm
Hybrid flow-shop
Genetic algorithm
Constraint programming
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Snippet The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a...
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SubjectTerms Algorithms
Computer Science
Data Mining and Knowledge Discovery
Genetic algorithms
Management Science
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Multiprocessing
Mutation
Operations Research
Optimization
Performance evaluation
Scheduling
Studies
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Title Hybrid Flow-Shop: a Memetic Algorithm Using Constraint-Based Scheduling for Efficient Search
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