A novel multiobjective optimization algorithm for 0/1 multiobjective knapsack problems
Min-Rong Chen, Jian Weng, Xia Li · 2010
This paper extends a novel numerical multiobjective optimization algorithm, so-called Multiobjective Extremal Optimization (MOEO), to solve the 0/1 multiobjective knapsack problems. The proposed approach is validated by three benchmark problems. The simulation results indicate that the proposed approach is highly competitive with three state-of-the-art multiobjective evolutionary algorithms, i.e., NSGA, SPEA and NPGA. Thus, MOEO can be considered a good alternative to solve the 0/1 multiobjective knapsack problems.