Title :
Investigation of memory-based multi-objective optimization evolutionary algorithm in dynamic environment
Author :
Wang, Yu ; Li, Bin
Author_Institution :
Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei
Abstract :
As the research of dynamic optimization arising, memory-based strategy has gained public attention recently. However, few studies on developing dynamic multi-objective optimization algorithms and even fewer studies on multi-objective memory-based strategy were reported previously. In this paper, we try to address such an issue by proposing several memory-based multi-objective evolutionary algorithms and experimentally investigating different multi-objective dynamic optimization schemes, which include restart, explicit memory, local search memory and hybrid memory schemes. This study is to provide pre-trial research of how to appropriately organize and effectively reuse the changed Pareto-optimal decision values (i.e., Pareto-optimal solutions: POS) information.
Keywords :
Pareto optimisation; decision theory; evolutionary computation; Pareto-optimal decision value; dynamic optimization; explicit memory scheme; hybrid memory scheme; localsearch memory scheme; memory-based strategy; multiobjective optimization evolutionary algorithm; Algorithm design and analysis; Convergence; Costs; Design optimization; Electronic design automation and methodology; Evolutionary computation; Genetic engineering; Heuristic algorithms; Robustness; Working environment noise;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983004