Title :
Pure and Hybrid Optimizers Applicable to Large-Scale Design Problem
Author_Institution :
Dept. of Mech. Syst. Eng., Hokkaido Inst. of Technol., Sapporo, Japan
Abstract :
Design-Informatics has three points of view. One of these points is the investigation of efficient optimization to generate hypothetical database for a large-scale design problem. the results of the present study indicates the hybrid method between differential evolution and genetic algorithm is better performance for efficient exploration in design space under the condition for large-scale engineering design problem within 102 order evolution at most.
Keywords :
design engineering; genetic algorithms; particle swarm optimisation; design-informatics; differential evolution; genetic algorithm; hybrid optimizers; large-scale engineering design problem; particle swarm optimization; pure optimizers; Evolutionary computation; Genetic algorithms; History; Measurement; Noise; Optimization; Sociology; design-informatics; differential evolution; evolutionary computation; genetic algorithm; hybrid optimizer; particle swarm optimization;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
DOI :
10.1109/ICGEC.2012.123