Less is more: Basic variable neighborhood search for minimum differential dispersion problem
In this paper, we propose a basic variable neighborhood search for solving Minimum differential dispersion problem using only the swap neighborhood structure in both descent (intensification) and shaking (diversification) steps. It has become a trend in the metaheuristic literature to use hybrid metaheuristics, i.e., combination of several metaheuristic paradigms, for solving some particular optimization problem. We show that our simple method, which relies on the basic Variable neighborhood search, significantly outperforms the hybrid one that combines GRASP, Variable neighborhood search, and Exterior path relinking metaheuristics. Thus, simplicity is not only the desired user friendly property of a heuristic but can lead to more efficient and effective method than if complex hybrid metaheuristic is used: less is more.
variable neighborhood search differential dispersion heuristic optimization