A Multiobjective Memetic Approach to Job-Shop Scheduling under Uncertainty

Tran, Thanh-Do; González-Rodríguez, Inés; Talbi, El-Ghazali

Document type :

Communication dans un congrès avec actes

Title :

A Multiobjective Memetic Approach to Job-Shop Scheduling under Uncertainty

Author(s) :

Tran, Thanh-Do [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
González-Rodríguez, Inés [Auteur]
Department of Mathematics, Statistics and Computing
Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]

Conference title :

The 5th International Conference on Metaheuristics and Nature Inspired Computing (META'14)

City :

Marrakech

Country :

Maroc

Start date of the conference :

2014-10-27

Publication date :

2014-10-27

English keyword(s) :

job-shop scheduling
multiobjective memetic algorithm
uncertainty
robustness analysis

HAL domain(s) :

Computer Science [cs]/Operations Research [math.OC]

English abstract : [en]

In recent years, much work has been expended on addressing job-shop scheduling problems (JSP) with uncertain information. There are two primary approaches to uncertainty handling, i.e. using probability theory and possibility ...
Show more >In recent years, much work has been expended on addressing job-shop scheduling problems (JSP) with uncertain information. There are two primary approaches to uncertainty handling, i.e. using probability theory and possibility theory. In this work, we use the possibilistic approach to deal with JSP where uncertain processing times are modeled by triangular fuzzy numbers (TFNs). Algorithmically, this paper examines the incorporation of a local search into a multiobjective genetic approach. The incorporation results in a simple multiobjective memetic algorithm that is based on the NSGA-II and the N2 neighborhood structure for individual improvement in the Lamarckian learning procedure. An extensive experiment was conducted to confirm the superiority of the algorithm compared to both the single-objective memetic and multiobjective genetic methods.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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