An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations
We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP). This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the mac...
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Growing Science
2016-09-01
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Online Access: | http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_12.pdf |
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doaj-a8d38b64b99f4ad883c0f57c7e9180922020-11-25T00:25:40ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342016-09-017458559610.5267/j.ijiec.2016.4.002An alternative hybrid evolutionary technique focused on allocating machines and sequencing operationsMariano FrutosFernando TohméFernando DelbiancoFabio Miguel We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP). This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA) and a path-dependent search algorithm (Multi-Objective Simulated Annealing), which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good. http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_12.pdfFlexible job-shop scheduling problemOptimizationMulti-objective hybrid Evolutionary algorithmProduction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mariano Frutos Fernando Tohmé Fernando Delbianco Fabio Miguel |
spellingShingle |
Mariano Frutos Fernando Tohmé Fernando Delbianco Fabio Miguel An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations International Journal of Industrial Engineering Computations Flexible job-shop scheduling problem Optimization Multi-objective hybrid Evolutionary algorithm Production |
author_facet |
Mariano Frutos Fernando Tohmé Fernando Delbianco Fabio Miguel |
author_sort |
Mariano Frutos |
title |
An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
title_short |
An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
title_full |
An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
title_fullStr |
An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
title_full_unstemmed |
An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
title_sort |
alternative hybrid evolutionary technique focused on allocating machines and sequencing operations |
publisher |
Growing Science |
series |
International Journal of Industrial Engineering Computations |
issn |
1923-2926 1923-2934 |
publishDate |
2016-09-01 |
description |
We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP). This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA) and a path-dependent search algorithm (Multi-Objective Simulated Annealing), which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good.
|
topic |
Flexible job-shop scheduling problem Optimization Multi-objective hybrid Evolutionary algorithm Production |
url |
http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_12.pdf |
work_keys_str_mv |
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