Adaptability of multirecombinated evolutionary algorithms to changing common due dates

In the restricted single-machine common due date problem, the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties. This problem, even in its simplest formulation, is an NP-Hard optimization problem. New trends to enhance evolutionary algor...

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Detalles Bibliográficos
Autores principales: Pandolfi, Daniel, Vilanova, Gabriela, San Pedro, María Eugenia de, Villagra, Andrea, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Evolutionary Algorithms
Single Machine Scheduling
Multirecombination
Common due date
Problem
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21650
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21650
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
Evolutionary Algorithms
Single Machine Scheduling
Multirecombination
Common due date
Problem
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
spellingShingle Ciencias Informáticas
Evolutionary Algorithms
Single Machine Scheduling
Multirecombination
Common due date
Problem
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Pandolfi, Daniel
Vilanova, Gabriela
San Pedro, María Eugenia de
Villagra, Andrea
Gallard, Raúl Hector
Adaptability of multirecombinated evolutionary algorithms to changing common due dates
topic_facet Ciencias Informáticas
Evolutionary Algorithms
Single Machine Scheduling
Multirecombination
Common due date
Problem
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
description In the restricted single-machine common due date problem, the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties. This problem, even in its simplest formulation, is an NP-Hard optimization problem. New trends to enhance evolutionary algorithms introduced multiple-crossovers-on-multiple-parents (MCMP) a multirecombinative approach allowing multiple crossovers on the selected pool of (more than two) parents. MCMP-V is a novel MCMP variant, which directly applies multirecombination to the Lee and Kim approach using uniform scanning crossover.
format Objeto de conferencia
Objeto de conferencia
author Pandolfi, Daniel
Vilanova, Gabriela
San Pedro, María Eugenia de
Villagra, Andrea
Gallard, Raúl Hector
author_facet Pandolfi, Daniel
Vilanova, Gabriela
San Pedro, María Eugenia de
Villagra, Andrea
Gallard, Raúl Hector
author_sort Pandolfi, Daniel
title Adaptability of multirecombinated evolutionary algorithms to changing common due dates
title_short Adaptability of multirecombinated evolutionary algorithms to changing common due dates
title_full Adaptability of multirecombinated evolutionary algorithms to changing common due dates
title_fullStr Adaptability of multirecombinated evolutionary algorithms to changing common due dates
title_full_unstemmed Adaptability of multirecombinated evolutionary algorithms to changing common due dates
title_sort adaptability of multirecombinated evolutionary algorithms to changing common due dates
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/21650
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