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

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3 Author(s)
Fatima Benbouzid-Sitayeb ; Lab. des Methodes de Conception de Syst., Algiers ; Christophe Varnier ; Nourredine Zerhouni

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

Published in:

2006 International Conference on Service Systems and Service Management  (Volume:1 )

Date of Conference:

Oct. 2006