Solving the Supply Management Problem by means of Genetic Algorithms
نویسنده
چکیده
This paper presents two variants of genetic algorithm for solving the Supply Management Problem, which can be viewed as a generalization of the Fixed Charge Transportation Problem. The first variant uses the usual binary representation of solutions. The second one is based on the permutation representation and the greedy decoder. Computational results indicate good performance of the second approach. In this paper, we consider the problem of planing the production flows from the set of providers to several consumers in order to minimize the total transportation costs. Unlike the classical transportation problem the considered one has nonlinear cost function and also there are additional restrictions on minimum quantity of the delivery. Let n be the number of providers, m be the number of consumers, Mi be the capacity of the provider i (i = 1, ..., n), Aj be the demand of the consumer j (j = 1, ...,m), aij and cij be the fixed and variable costs respectively. The model of the supply management problem (SMP) is as follows:
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