DocumentCode :
2690028
Title :
Enhanced differential evolution hybrid scatter search for discrete optimization
Author :
Davendra, Donald ; Onwubolu, Godfrey
Author_Institution :
Tomas Bata Univ., Zlin
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
1156
Lastpage :
1162
Abstract :
A hybrid approach of the enhanced differential evolution (EDE) and scatter search (SS), termed HEDE-SS, is presented in order to solve discrete domain optimization problems. This approach is envisioned in order to capture the randomization properties of EDE and the memory adaptation programming (MAP) properties of SS. Two highly demanding problems of quadratic assignment problem (QAP) and traveling salesman problem (TSP) are optimized with this new heuristic approach. The hybrid obtains the optimal results for almost all of the QAP instances, compares very well for symmetric TSP by getting results around 98 per cent to the optimal.
Keywords :
evolutionary computation; travelling salesman problems; discrete domain optimization; enhanced differential evolution; hybrid scatter search; memory adaptation programming; quadratic assignment problem; traveling salesman problem; Evolutionary computation; Scattering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4424600
Filename :
4424600
Link To Document :
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