Incorporating domain-specific heuristics in a particle swarm optimization approach to the quadratic assignment problem

摘要: We propose two variations on particle swarm optimization (PSO): the use of a heuristic function as an additional biasing term in PSO solution construction; and local search step algorithm. apply these to hierarchical model evaluate them quadratic assignment problem (QAP). compare performance our method diversified-restart robust tabu (DivTS), one leading approaches at present for QAP. Our experimental results, using instances from QAPLIB instance library, indicate that approach performs competitively with DivTS.