How to keep good schemata using cross-over operators for permutation problems

Djerid, Lamia; Portmann, Marie-Claude

doi:10.1016/s0969-6016(00)00038-1

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Crossover Procedures1

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2006

2014

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Cited by 4 publications

(2 citation statements)

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“…Children are generated by exchanging parents' strings. However, in BCP the only difference between an individual and another is the order in which the elements of the chromosome are permuted, and in most cases it makes no sense to talk of pure recombination (Djerid & Portmann, 2000), since the association of different parents would generate infeasible solutions (doubling some positions and excluding others). Therefore BCP is better suited by an operator such as the linear order crossover operator (Davis, 1985, pp.…”

Section: Crossover Proceduresmentioning

confidence: 99%

An application of the vehicle routing problem to biomass transportation

Gracia

Velázquez‐Martí

Estornell

2014

Biosystems Engineering

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Section: Crossover Proceduresmentioning

confidence: 99%

An application of the vehicle routing problem to biomass transportation

Gracia

Velázquez‐Martí

Estornell

2014

Biosystems Engineering

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“…Some different encodings are proposed in the literature [20,21]. These encodings are split into two categories.…”

Section: ))mentioning

confidence: 99%

Proposition of New Genetic Operator for Solving Joint Production and Maintenance Scheduling: Application to the Flow Shop Problem

Benbouzid-Sitayeb¹,

Varnier²,

Zerhouni³

2006

2006 International Conference on Service Systems and Service Management

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Genetic algorithms are used in scheduling leading to efficient heuristic methods for large sized problems. The efficiency of a GA based heuristic is closely related to the quality of the used GA scheme and the GA operators: mutation, selection and crossover. In this paper, we propose a Joint Genetic Algorithm (JGA), for joint production and maintenance scheduling problem in permutation flowshop, in which different genetic joint operators are used. We also proposed a joint structure to represent an individual in with two fields: the first one for production data and the second one for maintenance data. We used different Taillard benchmarks to compare the performances of JGA with each proposed operator.

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