Title :
A novel multiobjective optimization algorithm for 0/1 multiobjective knapsack problems
Author :
Chen, Min-Rong ; Weng, Jian ; Li, Xia
Author_Institution :
Coll. of Inf. Eng., Shenzhen Univ., Shenzhen, China
Abstract :
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.
Keywords :
evolutionary computation; knapsack problems; optimisation; 0/1 multiobjective knapsack problems; NPGA; NSGA; SPEA; evolutionary algorithms; multiobjective extremal optimization; multiobjective optimization algorithm; Computer science; Ecosystems; Educational institutions; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Mathematical programming; Nearest neighbor searches; Pareto optimization; Simulated annealing; 0/1 multiobjective knapsack problems; multiobjective extremal optimization; multiobjective optimization;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-5045-9
Electronic_ISBN :
978-1-4244-5046-6
DOI :
10.1109/ICIEA.2010.5514668
