Skip to Main content Skip to Navigation
Conference papers

Hybrid genetic algorithm for bi-objective assignment problem

Abstract : We propose a hybrid approach for multi-objective assignment problem which combines genetic algorithm and mathematical programming techniques. This method is based on the dominance cost variant of the multi-objective genetic algorithm hybridized with exact method. The initial population is generated by solving a series of mono-objective assignment problems obtained by a suitable choice of a set of weights. The crossover operator solves a reduced mono-objective problem where the weights are chosen to identify an unexplored region. Numerical experiments show the efficiency of our approach.
Document type :
Conference papers
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03473054
Contributor : Kathleen TORCK Connect in order to contact the contributor
Submitted on : Thursday, December 9, 2021 - 4:41:03 PM
Last modification on : Monday, March 28, 2022 - 4:04:38 PM

Identifiers

  • HAL Id : hal-03473054, version 1

Collections

Citation

Mustapha Ratli, Mansour Eddaly, Bassem Jarboui, Sylvain Lecomte, Said Hanafi. Hybrid genetic algorithm for bi-objective assignment problem. International Conference on Industrial Engineering and Systems Management (IEEE-IESM'2013), Oct 2013, Rabat, Morocco. ⟨hal-03473054⟩

Share

Metrics

Record views

21