A PSO-Based Hybrid Multi-Objective Algorithm for Multi-Objective Optimization Problems


This paper proposes a PSO-based hybrid multi-objective algorithm (HMOPSO) with the following three main features. First, the HMOPSO takes the crossover operator of the genetic algorithm as the particle updating strategy. Second, a propagating mechanism is adopted to propagate the non-dominated archive. Third, a local search heuristic based on scatter search is applied to improve the non-dominated solutions. Computational study shows that the HMOPSO is competitive with previous multi-objective algorithms in literature.