Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems

In previous works the ability of CPS-MCPC (an evolutionary, co-operative, population search method with multiple crossovers per couple) to build well delineated Pareto fronts in diverse multiobjective optimization problems (MOOPs) was demonstrated. To test the potential of the novel method when deal...

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Autores principales: Esquivel, Susana Cecilia, Ferrero, Sergio W., Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Scheduling
Optimization
ARTIFICIAL INTELLIGENCE
Evolutionary Computation
Job shop scheduling
multiobjective optimization
multirecombination
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23406
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23406
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Scheduling
Optimization
ARTIFICIAL INTELLIGENCE
Evolutionary Computation
Job shop scheduling
multiobjective optimization
multirecombination
spellingShingle Ciencias Informáticas
Scheduling
Optimization
ARTIFICIAL INTELLIGENCE
Evolutionary Computation
Job shop scheduling
multiobjective optimization
multirecombination
Esquivel, Susana Cecilia
Ferrero, Sergio W.
Gallard, Raúl Hector
Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
topic_facet Ciencias Informáticas
Scheduling
Optimization
ARTIFICIAL INTELLIGENCE
Evolutionary Computation
Job shop scheduling
multiobjective optimization
multirecombination
description In previous works the ability of CPS-MCPC (an evolutionary, co-operative, population search method with multiple crossovers per couple) to build well delineated Pareto fronts in diverse multiobjective optimization problems (MOOPs) was demonstrated. To test the potential of the novel method when dealing with the Job Shop Scheduling Problem (JSSP), regular and non-regular objectives functions were chosen. They were the makespan and the mean absolute deviation (of job completion times from a common due date, an earliness/tardiness related problem). Diverse representations such as priority list representation (PLR), job-based representation (JBR) and operation-based representation (OBR) among others were implemented and tested. The latter showed to be the best one. As a good parameter setting can enhance the behaviour of an evolutionary algorithm distinct parameters combinations were implemented and their influence studied. Multiple crossovers on multiple parents (MCMP), a powerful multirecombination method showed some enhancement in single objective optimization when compared with MCPC. This paper shows the influence of different recombination schemes when building the Pareto front under OBR and using the best parameter settings determined in previous works on a set of demonstrative Lawrence´s instances. Details of implementation and results are discussed.
format Objeto de conferencia
Objeto de conferencia
author Esquivel, Susana Cecilia
Ferrero, Sergio W.
Gallard, Raúl Hector
author_facet Esquivel, Susana Cecilia
Ferrero, Sergio W.
Gallard, Raúl Hector
author_sort Esquivel, Susana Cecilia
title Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
title_short Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
title_full Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
title_fullStr Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
title_full_unstemmed Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
title_sort upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/23406
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AT ferrerosergiow upgradingevolutionaryalgorithmsthroughmultiplicityformultiobjectiveoptimizationinjobshopschedulingproblems
AT gallardraulhector upgradingevolutionaryalgorithmsthroughmultiplicityformultiobjectiveoptimizationinjobshopschedulingproblems
bdutipo_str Repositorios
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