A multi-objective membrane algorithm for knapsack problems

This paper proposes a multi-objective membrane algorithm, called MOMA, for solving multi-objective knapsack problems. MOMA is designed with the framework and rules of a cell-like P system, and concepts and principles of quantum-inspired evolutionary algorithms. Three bench knapsack problems used frequently in the literature are applied to test MOMA performance. Experimental results show that MOMA outperforms its counterpart quantum-inspired evolutionary algorithm and several good multi-objective evolutionary algorithms reported in the literature, in terms of Pareto front and performance measures.