![]() ; Toro Pozo, Jorge Luis ![]() in Annals of Operations Research (2016) In this article we introduce a new multiobjective optimizer based on a recently proposed metaheuristic algorithm named Variable Mesh Optimization (VMO). Our proposal (multiobjective VMO, MOVMO) combines ... [more ▼] In this article we introduce a new multiobjective optimizer based on a recently proposed metaheuristic algorithm named Variable Mesh Optimization (VMO). Our proposal (multiobjective VMO, MOVMO) combines typical concepts from the multiobjective optimization arena such as Pareto dominance, density estimation and external archive storage. MOVMO also features a crossover operator between local and global optima as well as dynamic population replacement. We evaluated MOVMO using a suite of four wellknown benchmark function families, and against seven state-of-the-art optimizers: NSGA-II, SPEA2,MOCell, AbYSS,SMPSO,MOEA/DandMOEA/D.DRA. The statistically validated results across the additive epsilon, spread and hypervolume quality indicators confirm that MOVMO is indeed a competitive and effective method for multiobjective optimization of numerical spaces. [less ▲] Detailed reference viewed: 145 (1 UL) |
||