A New Parallel Cooperative Model for Trajectory Based Metaheuristics

摘要

This paper proposes and studies the behavior of a new parallel cooperative model for trajectory based metaheuristics. Algorithms based on the exploration of the neighborhood of a single solution like simulated annealing (SA) have offered very accurate results for a large number of real-world problems. Although this kind of algorithms are quite efficient, more improvements are needed to address the large temporal complexity of industrial problems. One possible way to improve the performance is the utilization of parallel methods. The field of parallel models for trajectory methods has not been deeply studied. The new proposed parallel cooperative model allows both to reduce the global execution time and to improve the efficacy. We have evaluated this model in two very different techniques (SA and PALS) solving a real-world problem (the DNA Fragment Assembly).