| Abstract:
Selecting the right suppliers significantly reduces the purchasing cost and improves the corporate competitiveness because in most industries the cost of raw materials and components parts constitutes the main cost of a product.
Little attention has been given in the literature to order assigning models to the suppliers, in case of multiple sourcing with multiple criteria and capacity constraints. Only a few mathematical programming models to analyses such decisions have been presented to date, and these have tended to consider only net price as the cost of purchasing although the costs of transportation, ordering and storage may be significantly important to the decisions.
In this paper, a mixed integer non-linear programming is presented to solve the multiple sourcing problems, which takes into account the total cost of logistics, including net price, storage, transportation and ordering costs.
Buyer limitations on budget, quality, storage capacity, integer number of orders, minimum assigned order quantity to each supplier, etc. are also taken into consideration in this model. Due to the complexity of the model and its non-linearity, the particular case of this study has been solved by genetic algorithm and its results have been compared to those of pattern search method.
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