Article

Computational Optimization and Applications

, Volume 44, Issue 3, pp 411-426

Hybrid heuristics for the maximum diversity problem

  • Micael GallegoAffiliated withDepartamento de Ciencias de la Computación, Universidad Rey Juan Carlos
  • , Abraham DuarteAffiliated withDepartamento de Ciencias de la Computación, Universidad Rey Juan Carlos
  • , Manuel LagunaAffiliated withLeeds School of Business, University of Colorado at Boulder
  • , Rafael MartíAffiliated withDepartamento de Estadística e Investigación Operativa, Universidad de Valencia Email author 

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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.