This paper seeks to identify the priority of factors affecting the quality of banking services in Bank Saderat Iran for better allocation of resources to enhance the quality of its banking services. The study develops a fuzzy method to handle uncertainty associated with the data and using analytical network process (ANP) ranks different factors influencing on service quality. The results have indicated that the quality of e-services (ESQ) is the most important factor followed by the quality of banking services agility (ASQ), the service system quality (SSQ), and the behavioral service qualities (BSQ). Moreover, the employees’ competence and skills, the reliability of the electronic system and the reliability of the service system, an impeccability banking system integrity and accountability instruments are among other effective factors influencing on the quality of banking services.

A key indicator to evaluate the success of an organization is the degree of meeting specific civil project goals based on a predetermined schedule. Therefore, the main purpose of this paper is to evaluate the performance of governmental administration agencies based on realization of civil project goals. In this paper, the information published by the President Deputy of Strategic Planning and Control, that publishes an annual report of evaluation indicators for national civil development projects, are used to evaluate and prioritize the major and non-major governmental agencies. Also, the Gray Relational Analysis (GRA) and the TOPSIS method are employed to analyze the data. The results indicate that using the GRA method, Supreme Council of Seminary and using the TOPSIS method, The Ministry of Labor and Social Affaires have gained the highest ranking.

In this paper, a robust bi-level model is proposed to optimize decisions related to distribution and evacuation aid after earthquake. Usually in disastrous situation foreign countries help the affected country by sending relief commodities. In this problem, the foreign countries try to minimize their shipping costs and the affected country seeks to minimize its total costs which include inventory, operation, and transportation expenses. This situation is a game between different decision makers after a catastrophic disaster. To deal with this situation, a bi-level model is proposed in which the affected country is the leader and suppliers are the followers. To validate the proposed robust model, we consider Tehran probable earthquake in region 1 as a case study. Then the advantages of using bi-level modeling against considering just one player's point of view is provided. The sensitivity analysis of the experiments are presented to explore the effects of various parameters to show managerial insights that can guide DMs under a variety of conditions.

The objective of this paper is to develop an integrated production inventory model for reworkable items with exponential demand rate. This is a three-layer supply chain model with perspectives of supplier, producer and retailer. Supplier delivers raw material to the producer and finished goods to the retailer. We consider perfect and imperfect quality products, product reliability and reworking of imperfect items. After screening, defective items reworked at a cost just after the regular manufacturing schedule. At the beginning, the manufacturing system starts produce perfect items, after some time the manufacturing system can undergo into “out-of-control” situation from “in-control” situation, which is controlled by reverse logistic technique. This paper deliberates the effects of business strategies like optimum order size of raw material, exponential demand rate, production rate is demand dependent, idle times and reverse logistics for an integrated marketing system. Mathematica is used to develop the optimal solution of production rate and raw material order for maximum expected average profit. A numerical example and sensitivity analysis is illustrated to validate the model.

In most industrial environments, it is usually considered that machines are accessible throughout the planning horizon, but in real situation, machines may be unavailable due to a scheduled preventive maintenance where the periods of unavailability are known in advance. The main idea of this paper is to consider different preventive maintenance policies on machines regarding open shop scheduling problem (OSSP) with sequence dependent setup times (SDST) using immune algorithm. The preventive maintenance (PM) policies are planned for maximizing availability of machines or keeping minimum level of reliability through the production horizon. The objective function of the paper is to minimize makespan. In total, the proposed algorithm extensively is compared with six adaptations of existing heuristic and meta-heuristic methods for the problem through data sets from benchmarks based on Taillard’s instances with some adjustments. The results show that the proposed algorithm outperforms other algorithms for this problem.

In this study an integrated model is proposed for the location inventory routing problem under uncertainty. This problem involves determining the location of distribution centers (DCs) in a three echelon supply chain. The DCs receive orders from the customer and according to a continuous review inventory replenishment policy place orders to the supplier. The products are directly shipped from the supplier to the DCs. The vehicles start from the DCs to fulfill the demands of the customers. Determining the routing of the vehicles is one of the decisions involved in this problem. The demands of customers are stochastically distributed and the capacity of DCs are limited. If one of the DCs undergo a disruption and is unable to fulfill the demands of the customers, shortage may occur. Moreover in the proposed model the shortage is considered as partial backlogging. This means that if shortage occurs, some of the orders result in lost sales and other orders are fulfilled in the next period. In order to optimally solve the proposed model a nonlinear integer programming (INLP) model is developed. However, since the problem is NP-hard, the mathematical formulation cannot be efficiently solved for large sized instances of the problem. Therefore an outer approximation method is developed to solve the problem more efficiently. The computational results show the efficiency of the proposed method.

Marketing strategies and proper inventory replenishment policies are often incorporated by enterprises to stimulate demand and maximize profit. The aim of this paper is to represent an integrated model for dynamic pricing and inventory control of deteriorating items. To reflect the dynamic characteristic of the problem, the selling price is defined as a time-dependent function of the initial selling price and the discount rate. In this regard, the price is exponentially discounted to compensate negative impact of the deterioration. The planning horizon is assumed to be infinite and the deterioration rate is time-dependent. In addition to price, the demand rate is dependent on advertisement as a powerful marketing tool. Several theoretical results and an iterative solution algorithm are developed to provide the optimal solution. Finally, to show validity of the model and illustrate the solution procedure, numerical results are presented.

Selection of robots from the several proposed alternatives is a very important and tedious task. Decision makers are not limited to one method and several methods have been proposed for solving this problem. This study presents Polygons Area Method (PAM) as a multi attribute decision making method for robot selection problem. In this method, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion. The results of this method are compared with other typical multiple attribute decision-making methods (SAW, WPM, TOPSIS, and VIKOR) by giving two examples. To find similarity in ranking given by different methods, Spearman’s rank correlation coefficients are obtained for different pairs of MADM methods. It was observed that the introduced method is in good agreement with other well-known MADM methods in the robot selection problem.

The purpose of this research is to investigate the relationship between stock market development, business cycle and risk of the banks. The statistical population of the study is all banks whose shares were accepted in Tehran Stock Exchange from 2010 to 2015. The study selects 10 banks, which were active throughout the entire research period on the stock market. The research data were extracted from the financial statements of the companies and analyzed using regression models based on panel data. The research findings show that there was a direct and significant relationship between stock market development and risk of banks. In addition, the effect of stock market development on risk of banks was different in the presence or absence of a crisis, and the financial crisis in banks reduced the impact of the financial development on the risk of banks. The results also show that during the periods of commercial boom, the effect of the financial market development on the risk of banks was more than the periods of the recession.