Hybrid heuristics for the maximum diversity problem

Authors:
Micael Gallego;Abraham Duarte;Manuel Laguna;Rafael Martí
Affiliations:
Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, Madrid, Spain;Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, Madrid, Spain;Leeds School of Business, University of Colorado at Boulder, Boulder, USA;Departamento de Estadística e Investigación Operativa, Universidad de Valencia, Valencia, Spain
Venue:
Computational Optimization and Applications
Year:
2009

Citing 5
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Abstract

The maximum diversity problem presents a challenge to solution methods based on heuristic optimization. We undertake the development of hybrid procedures within the scatter search framework with the goal of uncovering the most effective designs to tackle this difficult but important problem. Our research revealed the effectiveness of adding simple memory structures (based on recency and frequency) to key scatter search mechanisms. Our extensive experiments and related statistical tests show that the most effective scatter search variant outperforms state-of-the-art methods.