InforLorV4, PascalFrancis, Corpus, bibRecord, 000147

Single row facility layout problem using a permutation-based genetic algorithm

Identifieur interne : 000147 ( PascalFrancis/Corpus ); précédent : 000146; suivant : 000148

Single row facility layout problem using a permutation-based genetic algorithm

Auteurs : Dilip Datta ; Andre R. S. Amaral ; Jose Rui Figueira

Source :

European journal of operational research [ 0377-2217 ] ; 2011.

RBID : Pascal:11-0302803

Descripteurs français

Pascal (Inist)
- Planning installation, Problème agencement, Permutation, Algorithme génétique, Problème NP difficile, En ligne, Coût, Système expert, Optimisation sans contrainte, Optimisation combinatoire, ..

English descriptors

KwdEn :
- Combinatorial optimization, Costs, Expert system, Genetic algorithm, Layout problem, NP hard problem, On line, Permutation, Plant layout, Unconstrained optimization.

Abstract

In this paper, a permutation-based genetic algorithm (GA) is applied to the NP-hard problem of arranging a number of facilities on a line with minimum cost, known as the single row facility layout problem (SRFLP). The GA individuals are obtained by using some rule-based as well as random permutations of the facilities, which are then improved towards the optimum by means of specially designed crossover and mutation operators. Such schemes led the GA to handle the SRFLP as an unconstrained optimization problem. In the computational experiments carried out with large-size instances of sizes from 60 to 80, available in the literature, the proposed GA improved several previously known best solutions.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A11	`02`	`1`		`@1 AMARAL (Andre R. S.)`
A11	`03`	`1`		`@1 RUI FIGUEIRA (Jose)`
A14	`01`			`@1 Department of Mechanical Engineering, National Institute of Technology-Silchar @2 Silchar 788 010 @3 IND @Z 1 aut.`
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A44				`@0 0000 @1 © 2011 INIST-CNRS. All rights reserved.`
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A64	`01`	`1`		`@0 European journal of operational research`
A66	`01`			`@0 NLD`
C01	`01`		`ENG`	@0 In this paper, a permutation-based genetic algorithm (GA) is applied to the NP-hard problem of arranging a number of facilities on a line with minimum cost, known as the single row facility layout problem (SRFLP). The GA individuals are obtained by using some rule-based as well as random permutations of the facilities, which are then improved towards the optimum by means of specially designed crossover and mutation operators. Such schemes led the GA to handle the SRFLP as an unconstrained optimization problem. In the computational experiments carried out with large-size instances of sizes from 60 to 80, available in the literature, the proposed GA improved several previously known best solutions.
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C03	`01`	`X`	`ENG`	`@0 Plant layout @5 06`
C03	`01`	`X`	`SPA`	`@0 Proyecto instalación @5 06`
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C03	`02`	`X`	`ENG`	`@0 Layout problem @5 07`
C03	`02`	`X`	`SPA`	`@0 Problema disposición @5 07`
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C03	`03`	`X`	`ENG`	`@0 Permutation @5 08`
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C03	`09`	`X`	`FRE`	`@0 Optimisation sans contrainte @5 14`
C03	`09`	`X`	`ENG`	`@0 Unconstrained optimization @5 14`
C03	`09`	`X`	`SPA`	`@0 Optimización sin restricción @5 14`
C03	`10`	`X`	`FRE`	`@0 Optimisation combinatoire @5 15`
C03	`10`	`X`	`ENG`	`@0 Combinatorial optimization @5 15`
C03	`10`	`X`	`SPA`	`@0 Optimización combinatoria @5 15`
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N21				`@1 206`
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Format Inist (serveur)

NO :	PASCAL 11-0302803 INIST
ET :	Single row facility layout problem using a permutation-based genetic algorithm
AU :	DATTA (Dilip); AMARAL (Andre R. S.); RUI FIGUEIRA (Jose)
AF :	Department of Mechanical Engineering, National Institute of Technology-Silchar/Silchar 788 010/Inde (1 aut.); CEG-IST, Center for Management Studies, Instituto Superior Técnico, Technical University of Lisbon, Tagus Park, Av. Cavaco Silva/2744-016 Porto Salvo/Portugal (1 aut., 2 aut.); INPL, Ecole des Mines de Nancy, Laboratoire LORIA, Parc de Saurupt CS 14 234/54 042 Nancy/France (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	European journal of operational research; ISSN 0377-2217; Coden EJORDT; Pays-Bas; Da. 2011; Vol. 213; No. 2; Pp. 388-394; Bibl. 1/2 p.
LA :	Anglais
EA :	In this paper, a permutation-based genetic algorithm (GA) is applied to the NP-hard problem of arranging a number of facilities on a line with minimum cost, known as the single row facility layout problem (SRFLP). The GA individuals are obtained by using some rule-based as well as random permutations of the facilities, which are then improved towards the optimum by means of specially designed crossover and mutation operators. Such schemes led the GA to handle the SRFLP as an unconstrained optimization problem. In the computational experiments carried out with large-size instances of sizes from 60 to 80, available in the literature, the proposed GA improved several previously known best solutions.
CC :	001D01A13; 001D01A04
FD :	Planning installation; Problème agencement; Permutation; Algorithme génétique; Problème NP difficile; En ligne; Coût; Système expert; Optimisation sans contrainte; Optimisation combinatoire; .
ED :	Plant layout; Layout problem; Permutation; Genetic algorithm; NP hard problem; On line; Costs; Expert system; Unconstrained optimization; Combinatorial optimization
SD :	Proyecto instalación; Problema disposición; Permutación; Algoritmo genético; Problema NP duro; En línea; Coste; Sistema experto; Optimización sin restricción; Optimización combinatoria
LO :	INIST-17566.354000192136780040
ID :	11-0302803

Links to Exploration step

Pascal:11-0302803

Le document en format XML

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<AF>Department of Mechanical Engineering, National Institute of Technology-Silchar/Silchar 788 010/Inde (1 aut.); CEG-IST, Center for Management Studies, Instituto Superior Técnico, Technical University of Lisbon, Tagus Park, Av. Cavaco Silva/2744-016 Porto Salvo/Portugal (1 aut., 2 aut.); INPL, Ecole des Mines de Nancy, Laboratoire LORIA, Parc de Saurupt CS 14 234/54 042 Nancy/France (3 aut.)</AF>
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<EA>In this paper, a permutation-based genetic algorithm (GA) is applied to the NP-hard problem of arranging a number of facilities on a line with minimum cost, known as the single row facility layout problem (SRFLP). The GA individuals are obtained by using some rule-based as well as random permutations of the facilities, which are then improved towards the optimum by means of specially designed crossover and mutation operators. Such schemes led the GA to handle the SRFLP as an unconstrained optimization problem. In the computational experiments carried out with large-size instances of sizes from 60 to 80, available in the literature, the proposed GA improved several previously known best solutions.</EA>
<CC>001D01A13; 001D01A04</CC>
<FD>Planning installation; Problème agencement; Permutation; Algorithme génétique; Problème NP difficile; En ligne; Coût; Système expert; Optimisation sans contrainte; Optimisation combinatoire; .</FD>
<ED>Plant layout; Layout problem; Permutation; Genetic algorithm; NP hard problem; On line; Costs; Expert system; Unconstrained optimization; Combinatorial optimization</ED>
<SD>Proyecto instalación; Problema disposición; Permutación; Algoritmo genético; Problema NP duro; En línea; Coste; Sistema experto; Optimización sin restricción; Optimización combinatoria</SD>
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Single row facility layout problem using a permutation-based genetic algorithm

Single row facility layout problem using a permutation-based genetic algorithm

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