دانلود مقاله ISI انگلیسی شماره 19176
ترجمه فارسی عنوان مقاله

FANP-MOLP یکپارچه برای ارزیابی تامین کننده و تخصیص سفارش

عنوان انگلیسی
An integrated FANP–MOLP for supplier evaluation and order allocation
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
19176 2009 7 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Mathematical Modelling, Volume 33, Issue 6, June 2009, Pages 2730–2736

ترجمه کلمات کلیدی
مدیریت زنجیره تامین () - برنامه ریزی خطی چند هدفه () - فرایند شبکه تحلیلی () - برنامه نویسی اولویت فازی () - انتخاب تامین کننده - () () - () - ()
کلمات کلیدی انگلیسی
Supply chain management (SCM), Multi-objective linear programming (MOLP), Analytic network process (ANP), Fuzzy preference programming (FPP), Supplier selection,
پیش نمایش مقاله
پیش نمایش مقاله  FANP-MOLP یکپارچه برای ارزیابی تامین کننده و تخصیص سفارش

چکیده انگلیسی

In the face of acute global competition, supplier management is rapidly emerging as a crucial issue to any companies striving for business success and sustainable development. To optimize competitive advantages, a company should incorporate “suppliers” as an essential part of its core competencies. Supplier evaluation, the first step in supplier management, is a complex multi-criteria decision-making (MCDM) problem, and its complexity is further aggravated if the highly important interdependence among the selection criteria is taken into consideration. The objective of this paper is to suggest a comprehensive decision method for identifying top suppliers by considering the effects of interdependence among the selection criteria, as well as to achieve optimal allocation of orders among the selected suppliers.

مقدمه انگلیسی

Due to the ever-mounting global competition, supplier management has come to play an increasingly crucial role as a key to business success. To secure competitive advantages, organizations have to integrate their internal core competencies and capabilities with those of their suppliers. How to choose capable suppliers is thus an imperative issue in the management of modern business organizations. Existing researches in the field of supplier selection can be divided into two major categories: those focusing on isolating different supply source selection criteria and assessing the degree of their importance from the purchasing firm’s point of view [1]; and those aiming to identify different alternative suppliers by developing and applying specific methods, such as cluster analysis [2], case based reasoning systems [3], statistical models [2], decision support systems [2] and [3], data envelopment analysis [2], [4] and [5], analytic hierarchy process [2] and [6], total cost of ownership models [2] and [7], activity based costing [8], artificial intelligence [2] and [3], and mathematical programming [9], [5] and [10]. Some of the above methods tend to treat each of the selection criteria and alternative suppliers as an independent entity. Price and quality, for example, are treated as two separate criteria without affecting each other. This is, however, seldom the case in the real world business context in which selection criteria and alternative suppliers are in fact characterized by interdependence. Analytic network process (ANP) can therefore be adopted to accommodate the concern of interdependence among selection criteria or alternatives. The ANP method recognizes only crisp comparison ratios. Yet human judgments are usually uncertain of its preferences. Mikhailov and Singh [11] utilizes the interval values to express the comparisons and develops the fuzzy preference programming (FPP) method to calculate the weight of every level for coping with inconsistent and uncertain judgments. The objective of this paper is to suggest a comprehensive decision method for identifying top suppliers by considering the effects of interdependence among the selection criteria, as well as to achieve optimal allocation of orders among the selected suppliers. The proposed method accordingly incorporates two stages: (i) Combine ANP with FPP into a more powerful FANP for selection of top suppliers, and (ii) Apply multi-objective linear programming (MOLP) to facilitate optimal allocation of orders.

نتیجه گیری انگلیسی

Supplier selection is a complex multi-criteria decision-making problem, and its complexity is further aggravated if the highly important interdependence among the selection criteria is taken into consideration. ANP, providing a systematic approach to set priorities among alternative suppliers, can effectively capture the interdependencies among various criteria. However, ANP handles only crisp comparison ratios. The FPP method is accordingly adopted as a supplement to increase the capability of ANP in tackling with uncertain decision-making judgments. Aiming to enhance both efficiency and accuracy, FANP that combines ANP and FPP can be adopted as an integrated model for supplier evaluation. Since each supplier has its own advantages and disadvantages in terms of cost, quality, service and the technology, a flexible method is required to take the limitations of the suppliers and the requirements of the buyers into consideration and to assist buyers in their decisions in optimal allocation of order quantity allocation. The integrated FANP–MOLP method can select the best set of multiple suppliers to satisfy all constraints. Although the proposed model reaches the same solutions as those of AHP–MOLP and ANP–MOLP methods, it is considered a better choice for its ability to take into account the interdependencies among various criteria and to deal with uncertain situations. The advantages of the integrated method include its abilities to: (1) Consider the interdependencies among various criteria and uncertain situation for ranking suppliers; (2) Minimize the end customer’s level of dissatisfaction based on demand and capacity limiting; and (3) Facilitate the most efficient allocation of an order. Our study, however, has not taken into consideration of certain common practices in real-life business transactions, such as the discount offered by a supplier for a huge order. Future studies may like to include such practices in the selection criteria to further enhance the accuracy in supplier selection.