Geodesic
Genetic Algorithm Approach for Solving the Task Assignment Problem
Serdica Journal of Computing, Tome 2 (2008) no. 3, pp. 267-276 Cet article a éte moissonné depuis la source Bulgarian Digital Mathematics Library

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In this paper a genetic algorithm (GA) for the task assignment problem (TAP) is considered.An integer representation with standard genetic operators is used. Computational results are presented for instances from the literature, and compared to optimal solutions obtained by the CPLEX solver. It can be seen that the proposed GA approach reaches 17 of 20 optimal solutions. The GA solutions are obtained in a quite a short amount of computational time.
Keywords: Evolutionary Approach, Genetic Algorithms, Assignment Problems, Multiprocessor Systems, Combinatorial Optimization 
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     author = {Savi\'c, Aleksandar and To\v{s}i\'c, Du\v{s}an and Mari\'c, Miroslav and Kratica, Jozef},
     title = {Genetic {Algorithm} {Approach} for {Solving} the {Task} {Assignment} {Problem}},
     journal = {Serdica Journal of Computing},
     pages = {267--276},
     year = {2008},
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     number = {3},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/SJC_2008_2_3_a3/}
}
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Savić, Aleksandar; Tošić, Dušan; Marić, Miroslav; Kratica, Jozef. Genetic Algorithm Approach for Solving the Task Assignment Problem. Serdica Journal of Computing, Tome 2 (2008) no. 3, pp. 267-276. http://geodesic.mathdoc.fr/item/SJC_2008_2_3_a3/