A diversified method for the multi-scenarios max-min knapsack problem

Abstract

In this paper, we propose a diversified method for tackling the multi-scenarios max-min knapsack problem. The proposed method is based on three phases: (i) the building phase, (ii) the combination phase and (iii) the exploring phase. The first phase yields a feasible solution by using a greedy procedure. The second phase tries to provide a new solution by combining subsets of starting solutions. The third phase tries to make an intensification in order to improve the solutions at hand. The proposed method is evaluated on a set of benchmark instances taken from the literature. The obtained results are compared to those reached by the best algorithms available in the literature. The results show that the proposed method provides better solutions than those already published.