Using hybrid optimization methods for the agro-food industry scheduling problem

The purpose of our works is the implementation of methodologies for the resolution of the agro-food industry scheduling problem. Three new approaches based on genetic algorithms are proposed to solve multi-objectives scheduling problems: sequential genetic algorithms (SGA), parallel genetic algorithms (PGA) and parallel sequential genetic algorithms (PSGA). Two high-level hybrid algorithms, SH_GA/TS et SH_GA/SA, are also proposed. The purpose in this hybridization is to benefit the exploration of the solution space by a population of individuals with the exploitation of solutions through a smart search of the local search algorithm

Data and Resources

Additional Info

Field Value
Source https://theses.hal.science/tel-00690465
Author Karray, Asma
Maintainer CCSD
Last Updated May 21, 2026, 00:31 (UTC)
Created May 21, 2026, 00:31 (UTC)
Identifier NNT: 2011ECLI0024
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS) ; Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)
creator Karray, Asma
date 2011-07-05T00:00:00
harvest_object_id d9adccc7-31b1-46b2-b5af-9c1766518221
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-30T00:00:00
set_spec type:THESE