Work

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

Year: 2006

Type: conference-paper

Abstract: 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

Source: International Conference on Service Systems and Service Management

DOI: 10.1109/icsssm.2006.320531

Authors: Fatima Benbouzid-Sitayeb, Christophe Varnier, Nourredine Zerhouni

Institution: Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2017298568

FWCI: 1.047

Cites: 22

Cited by: 4

Related to: 10