Bee colony optimization for robust solutions of multi-objective knapsack problems

Abstract

In the multi-objective optimization problems, errors due to parameter variations may occur in the real world, and it is useful to find a solution that minimizes such errors. Solutions with high stability against such uncertainties are called robust solutions.

In this study, we propose a bee colony optimization algorithm for finding robust Pareto optimal solutions to the multi-objective knapsack problem. We implement the proposed method in an
experimental environment to verify the usefulness of the proposed method. In this experiment, we compare the proposed method with an existing algorithm and show that our proposed algorithm obtains a better robust Pareto optimal solution for the multiobjective knapsack problem.