Path relinking in pareto multi-objective genetic algorithms

Authors:
Matthieu Basseur;Franck Seynhaeve;El-Ghazali Talbi
Affiliations:
Laboratoire d'Informatique Fondamentale de Lille (LIFL), UMR CNRS 8022, University of Lille, Villeneuve d'Ascq Cedex, France;Laboratoire d'Informatique Fondamentale de Lille (LIFL), UMR CNRS 8022, University of Lille, Villeneuve d'Ascq Cedex, France;Laboratoire d'Informatique Fondamentale de Lille (LIFL), UMR CNRS 8022, University of Lille, Villeneuve d'Ascq Cedex, France
Venue:
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Year:
2005

Citing 11
Cited 4

Introduction to algorithms

Introduction to algorithms
Minimizing total tardiness on one machine is NP-hard

Mathematics of Operations Research
Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems
Simultaneously Applying Multiple Mutation Operators in Genetic Algorithms

Journal of Heuristics
Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization

EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
A Hybrid Evolutionary Approach for Multicriteria Optimization Problems: Application to the Flow Shop

EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics

Journal of Heuristics
Design of multi-objective evolutionary algorithms: application to the flow-shop scheduling problem

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Muiltiobjective optimization using nondominated sorting in genetic algorithms

Evolutionary Computation
Genetic algorithms, path relinking, and the flowshop sequencing problem

Evolutionary Computation

A population-based local search for solving a bi-objective vehicle routing problem

EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Local search guided by path relinking and heuristic bounds

EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Solving a bi-objective flowshop scheduling problem by pareto-ant colony optimization

ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Solving bi-objective flow shop problem with hybrid path relinking algorithm

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Path relinking algorithms have proved their efficiency in single objective optimization. Here we propose to adapt this concept to Pareto optimization. We combine this original approach to a genetic algorithm. By applying this hybrid approach to a bi-objective permutation flow-shop problem, we show the interest of this approach. In this paper, we present first an Adaptive Genetic Algorithm dedicated to obtain a first well diversified approximation of the Pareto set. Then, we present an original hybridization with Path Relinking algorithm, in order to intensify the search between solutions obtained by the first approach. Results obtained are promising and show that cooperation between these optimization methods could be efficient for Pareto optimization.