Title :
Solving multiple-objective optimization problems using GISMOO algorithm
Author :
Zinflou, Arnaud ; Gagné, Caroline ; Gravel, Marc
Author_Institution :
Dept. d´´Inf. et de Math., Univ. du Quebec a Chicoutimi, Chicoutimi, QC, Canada
Abstract :
In this paper, we proposed a new Pareto generic algorithm which hybridizes genetic algorithm and artificial immune systems. Numerical experiments were made using a classical benchmark in multiple-objective optimization (MOKP). Results show that our approach is able to obtain better performance than two state of the art approaches: NSGAII and PMSMO.
Keywords :
Pareto optimisation; artificial immune systems; genetic algorithms; knapsack problems; GISMOO algorithm; NSGAII; PMSMO; Pareto generic algorithm; artificial immune systems; genetic algorithm hybridization; knapsack problem; multiple-objective optimization problems; Artificial immune systems; Calibration; Cloning; Constraint optimization; Density measurement; Design optimization; Evolutionary computation; Genetic algorithms; Iterative algorithms; Pareto optimization; MOKP; Pareto front; artificial immune systems; evolutionnary algorithm; hybridization; multiple-objective optimization;
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
DOI :
10.1109/NABIC.2009.5393704
