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One of the most important operational issues in urban drinking water production and distribution systems is to assign a plan for running hours of water supplying electric pumps. The cost of consuming electricity in these pumps allocates most of water and wastewater companies operational costs to itself which is dependent to their running hours. In this paper, meanwhile having a field study in Sistan rural water and wastewater company, the constraints for specifying electric pumps operational time in water supplying resources such as restrictions in fulfilling demand, supply potable water with suitable quality and uselessness of electric pumps have been identified. Due to uncertainty and fuzziness of the constraints, a linear programming model with fuzzy restrictions for determining electric pumps running hours per day is submitted with the aim to minimize electricity consumption and cost. After collecting and using required data for model, it proved that using the proposed model could reduce the costs of electrical energy and increase productivity up to 23 percent per month. The proposed mathematical fuzzy programming is able to specify electric pumps scheduling plan for water supply resources with the aim to reduce the costs of consuming energy.

Quality of products and services is considered as a key factor for customer satisfaction. Quality function deployment (QFD) is known as a critical tool for translating voice of customers to prioritize technical requirements of a production. The level of this satisfaction depends on the number of fulfilled requirements. It should be noted that this level varies according to the possible constraints. This paper aims to maximize customer satisfaction based on the possible limitations by using a fuzzy linear programming model. In this regard, customer requirements are prioritized by using fuzzy Delphi method and then the problem is changed to a linear programming model considering to the possible relationships in QFD. The proposed model is used as a case study for construction industry. After runnig the model, the percentage of optimal performance for each of the technical production requirements is defined.

One area of importance in Supply Chain Management Which has always been targeted by researchers is evaluating and selecting the suppliers. This article employs a mixed model of Fuzzy analytical hierarchy process and Fuzzy mathematical planning to assess and hand-pick suppliers of a car parts manufacturer. This model consists of two steps. In the first step, suppliers' total utility has been measured considering 13 factors, Fuzzy analytical hierarchy process has been applied in this stage. In the second step using a Fuzzy mathematical planning model we recognized suppliers' optimum purchasing basket. The algorithm used in analytical hierarchy process is Mikhailov algorithm which presents various advantages namely compatibility index, presenting a definite weight vector, and applicable with incomplete matrix. The result of the article show that applying this model will enable decision makers-merging quantitative and non quantitative criteria-not only to improve the quality of their decisions but also to be well assured of their course of actions.