DocumentCode :
2926129
Title :
Genetic algorithms for the fixed charge transportation problem
Author :
Gottlieb, Jens ; Paulmann, Lutz
Author_Institution :
Inst. fur Inf., Tech. Univ. Clausthal, Germany
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
330
Lastpage :
335
Abstract :
Two genetic algorithms (GAs) are presented for the fixed charge transportation problem (FCTP). Both algorithms incorporate knowledge about the properties of optimal solutions. The algorithms mainly differ in the technique used to deal with the inherent constraints of FCTP: while the GA based on the permutation representation can be classified as a decoder approach, the matrix representation resembles direct solution encoding with specialized operators to maintain feasibility. The authors compare both GAs on randomly generated instances. The simulations indicate the suitability of the approaches-in particular of the matrix representation-and demonstrate their superiority to a GA which has been proposed for transportation problems
Keywords :
genetic algorithms; matrix algebra; simulation; transportation; decoder approach; direct solution encoding; fixed charge transportation problem; genetic algorithms; matrix representation; optimal solutions; permutation representation; randomly generated instances; simulations; specialized operators; Capacity planning; Costs; Decoding; Encoding; Equations; Genetic algorithms; Linear programming; Polynomials; Transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
Type :
conf
DOI :
10.1109/ICEC.1998.699754
Filename :
699754
Link To Document :
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