Experiments on Neighborhood Combination Strategies for Bi-objective Unconstrained Binary Quadratic Programming Problem.

Local search is known to be a highly effective metaheuristic framework for solving a number of classical combinatorial optimization problems, which strongly depends on the characteristics of neighborhood structure. In this paper, we integrate the neighborhood combination strategies into the hypervolume-based multi-objective local search algorithm, in order to deal with the bi-objective unconstrained binary quadratic programming problem. The experimental results show that certain combinations are superior to others. The performance analysis sheds lights on the ways to further improvements.