سال:1393 | دوره: | شماره: |تعداد مقالات:2

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Quality function deployment (QFD) is a customer-driven approach, widely used to develop or process new product in order to maximize customer satisfaction. Last researches used linear physical programming (LPP) procedure to optimize QFD; however, QFD issue involved uncertainties, or fuzziness, which requires taking them into account for more realistic study. In this paper a set of fuzzy data is used to address linguistic values parameterized by triangular fuzzy numbers. The proposed integrated approach includes analytic hierarchy process (AHP), QFD, and LPP to maximize overall customer satisfaction under uncertain conditions and apply them in the supplier development problem. The fuzzy AHP (FAHP) approach is adopted as a powerful method to obtain the relationship between the customer requirements (CRs) and engineering characteristics (ECs) to construct the house of quality (HOQ) in QFD method. LPP is used to obtain the optimal achievement level of the ECs and subsequently the customer satisfaction level under different degrees of uncertainty. The effectiveness of proposed method will be illustrated by an example.