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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Main Authors: Mariano Frutos, Fernando Tohmé, Fernando Delbianco, Fabio Miguel
Format: Article
Language:English
Published: Growing Science 2016-09-01
Series:International Journal of Industrial Engineering Computations
Subjects:
Online Access:http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_12.pdf
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spelling 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
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