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Abstract
The object of this research is to solve assignment problem (AP) with genetic
algorithm. The AP is solved by travelling salesman problem (TSP) approach. It can be done,
because there is a similarity between representation of AP solution and representation TSP
solution. There are two operators in TSP can be applied in AP, those are crossover operator
and mutation operator. The experiments show that TSP approach can find the solutions of
AP. In this research, the Genetic Algorithm is implemented with order crossover and
reciprocal exchange mutation. According to this research, it can be concluded that the
software with modification of genetic algorithm to solve TSP, can give alternative optimum
solution of AP.
Keywords: assignment problem, crossover, genetic algorithm, mutation, travelling
salesman problem.
algorithm. The AP is solved by travelling salesman problem (TSP) approach. It can be done,
because there is a similarity between representation of AP solution and representation TSP
solution. There are two operators in TSP can be applied in AP, those are crossover operator
and mutation operator. The experiments show that TSP approach can find the solutions of
AP. In this research, the Genetic Algorithm is implemented with order crossover and
reciprocal exchange mutation. According to this research, it can be concluded that the
software with modification of genetic algorithm to solve TSP, can give alternative optimum
solution of AP.
Keywords: assignment problem, crossover, genetic algorithm, mutation, travelling
salesman problem.