مدل چند هدفه فازی افزایشی وزنی برای مشکل انتخاب تامین کننده تحت معافیت های قیمتی در یک زنجیره تامین
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|19188||2009||10 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 121, Issue 2, October 2009, Pages 323–332
Supplier selection is one of the most critical activities of purchasing management in a supply chain, because of the key role of supplier's performance on cost, quality, delivery and service in achieving the objectives of a supply chain. Supplier selection is a multiple-criteria decision-making (MCDM) problem that is affected by several conflicting factors. Depending on the purchasing situations, criteria have varying importance and there is a need to weight criteria. In practice, for supplier selection problems, most of the input information is not known precisely. In these cases, the theory of fuzzy sets is one of the best tools for handling uncertainty. The fuzzy multiobjective model is formulated in such a way as to simultaneously consider the imprecision of information and determine the order quantities to each supplier based on price breaks. The problem includes the three objective functions: minimizing the net cost, minimizing the net rejected items and minimizing the net late deliveries, while satisfying capacity and demand requirement constraints. In order to solve the problem, a fuzzy weighted additive and mixed integer linear programming is developed. The model aggregates weighted membership functions of objectives to construct the relevant decision functions, in which objectives have different relative importance. A numerical example is given to illustrate how the model is applied. Finally, the conclusions and recommendations are presented.
Organizations must pursue strategies to achieve higher quality, reduced costs and shorter lead times to maintain a competitive position in the global market. Within new strategies for purchasing and manufacturing, suppliers play a key role in achieving corporate competition. Hence, selecting the right suppliers is a vital component of these strategies. Supplier selection is a multiple-criteria decision-making (MCDM) problem that is affected by several conflicting factors. Consequently, a purchasing manager must analyze the trade-off among the several criteria. MCDM techniques support the decision makers (DMs) in evaluating a set of alternatives. In real situation, for supplier selection problems, the weights of criteria are different and depend on purchasing strategies in a supply chain (Wang et al., 2004). It is a common practice for suppliers to offer quantity discounts to encourage the buyer towards larger order. In this case, the buyer must decide what order quantities to assign to each supplier. This is a complicated multiobjective decision-making problem affected by several conflicting factors. In a real situation, for a supplier selection problem, most of the input information is not known precisely. At the time of making decisions, the value of many criteria and constraints are expressed in vague terms such as “very high in quality” or “low in price”. Deterministic models cannot easily take this vagueness into account. In these cases, the theory of fuzzy sets is one of the best tools to handle uncertainty. Fuzzy set theories are employed due to the presence of vagueness and imprecision of information in the supplier selection problem. In this paper, a fuzzy multiobjective model has been developed for the supplier selection problem under price breaks that depend on the sizes of order quantities. Through this model, purchase managers can assign different weights for numbers of criteria in order to manage flow of supply materials, components and finished products to improve quality, service and reduced cost, in order to make improvement in supply chain performance. This model can be used as a decision support system by the purchasing manager to decide what order quantities to place with each supplier in the case of multiple sourcing. The paper has the following structure. Section 2 presents a brief literature review of the quantitative approaches related to a supplier selection problem. Section 3 provides the necessary background of mixed binary integer programming and multiobjective supplier selection problem under price breaks that depend on the sizes of order quantities. Section 4 presents the weighted additive method to generate optimal solutions in a fuzzy environment. Section 5 gives a numerical example and reports the results of computational experiments. Finally, section 6 is devoted to conclusions and recommendations.
نتیجه گیری انگلیسی
Supplier selection is a MCDM in which the objectives are not equally important. In real cases, many input data are not known precisely for decision making. Simultaneously, in this model, vagueness of input data and varying importance of criteria are considered. The proposed model can help the DM to find out the appropriate order to each supplier, and allows purchasing manager(s) to manage supply chain performance on cost, quality, service, etc. The selection process is influenced by the suppliers’ price breaks, which depend on the sizes of order quantities. This model enables the management to reflect corporate strategies in the purchasing activities. Volume discount in a multiple-product, multiple-supplier competitive sourcing environment and inventory management of purchased items are still open for further investigations. This approach represents different aspects of the supplier selection problem in the real world. Moreover, the fuzzy multiobjective supplier selection problem is transformed into a convex (weighted additive) fuzzy programming model and its equivalent crisp single-objective LP programming. This transformation reduces the dimension of the system, giving less computational complexity, and makes the application of fuzzy methodology more understandable. Non-linearity in the supplier selection problem, membership function and fuzzy weights are still open for further investigations.