DocumentCode :
2709738
Title :
Improving the Performance of Genetic Algorithm in Capacitated Vehicle Routing Problem using Self Imposed Constraints
Author :
Ursani, Ziauddin ; Sarker, Ruhul ; Abbass, Hussein A.
Author_Institution :
Sch. of Inf. Technol. & Electr. Eng., New South Wales Univ., Canberra, ACT
fYear :
2007
fDate :
1-5 April 2007
Firstpage :
220
Lastpage :
225
Abstract :
The capacitated vehicle routing problem (CVRP) is a well known member of the family of NP hard problems. In the past few decades, a number of heuristics was introduced to solve this problem but no heuristic can claim to work well in all possible scenarios. In the literature, genetic algorithm (GA) even lags behind the other heuristics. In this paper, we reveal some of the reasons for the inferior performance of GA, and propose a number of mechanisms to improve its performance. A number of test problems are solved to demonstrate the usefulness of the algorithm.
Keywords :
computational complexity; constraint theory; genetic algorithms; transportation; vehicles; NP hard problems; capacitated vehicle routing problem; genetic algorithm; self imposed constraints; Australia; Computational intelligence; Genetic algorithms; Information technology; Intelligent vehicles; NP-hard problem; Performance analysis; Processor scheduling; Routing; Vehicle driving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Scheduling, 2007. SCIS '07. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0704-4
Type :
conf
DOI :
10.1109/SCIS.2007.367693
Filename :
4218620
Link To Document :
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