Title :

Adaptive multi-operator metaheuristics for quadratic assignment problems

Author(s) :

Drugan, Madalina [Auteur]
Vrije Universiteit Brussel [Bruxelles] [VUB]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Scientific editor(s) :

A. Tantar et al.

Book title :

EVOLVE – A bridge between probability, set oriented numerics and evolutionary algorithms

Publisher :

Springer

Publication date :

2014

English keyword(s) :

Local Search
Mutation Operator
Variable Neighbourhood Search
Local Search Algorithm
Quadratic Assignment Problem

HAL domain(s) :

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

English abstract : [en]

Local search based algorithms are a general and computational efficient metaheuristic. Restarting strategies are used in order to not be stuck in a local optimum. Iterated local search restarts the local search using ...
Show more >Local search based algorithms are a general and computational efficient metaheuristic. Restarting strategies are used in order to not be stuck in a local optimum. Iterated local search restarts the local search using perturbator operators, and the variable neighbourhood search alternates local search with various neighbourhoods. These two popular restarting techniques, or operators, evolve independently and are disconnected. We propose a metaheuristic framework, we call it <i>multi-operator metaheuristics</i>, which allows the alternative or simultaneously usage of the two restarting methods. Tuning the parameters, i.e. the neighbourhood size and the perturbation rate, is essential for the performance of metaheuristics. We automatically adapt the parameters for the two restarting operators using variants of <i>adaptive pursuit</i> for the multi-operators metaheuristic algorithms. We experimentally study the performance of several instances of the new class of metaheuristics on the quadratic assignment problem (QAP) instances, a well-known and difficult combinatorial optimization problem.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Collections :

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

Source :

Harvested from HAL