In this paper, we study a reverse supply chain consists of three layers of the supply chain including suppliers, producers and customers by considering customers’ requirements. In the customer layer, we analyze the customer’s data to identify and fulfill their needs by collecting a list of customers’ views into consideration. In this case, the proposed model analyzes the customers view in the three areas of transport, production and quality and it uses the coding system for getting customers’ opinions. Then, by using the K-means algorithm, which is one of the data analyzing algorithms, the proposed model clusters the data so that similar data enter to the same cluster. The mathematical model is developed for each of the categories and Lingo software package is employed to solve the resulted problem in each category.

Environmental legislation and customer expectations force manufactures to take back their products after use. In this paper a recovery system for a single item is studied, in which the random returns depend on the demand stream. The model is different from other works in this field by considering the effect of disposal cost at the end of the planning horizon, on the total inventory cost. The proposed model of this paper explains how to change the reorder point to maintain the optimal policy. The paper is also supported with some numerical example to demonstrate the implementation of the optimal reordering policy.

Data Envelopment Analysis (DEA) has been widely used as an effective tool for measuring the relative efficiency of similar units by considering various input/output parameters. This paper examines DEA models for the estimation and improvement of organizational inputs and outputs in order to enhance management and decision making processes. We propose an empirical DEA analysis on banking sector by considering several financial and non-financial inputs and outputs. The relative efficiencies of various branches of banks are analyzed in different scenarios. The preliminary results indicate that there are some non-financial items that could significantly change the overall performance of a unit along with other financial items.

During the past few years, there have tremendous efforts on improving the cost of logistics using varieties of Vehicle Routing Problem (VRP) models. In fact, the recent rise on fuel prices has motivated many to reduce the cost of transportation associated with their business through an improved implementation of VRP systems. We study a specific form of VRP where demand is supposed to be uncertain with unknown distribution. A Particle Swarm Optimization (PSO) is proposed to solve the VRP and the results are compared with other existing methods. The proposed approach is also used for real world case study of drug distribution and the preliminary results indicate that the method could reduce the unmet demand significantly.

During the past few decades, there have been many evidences to believe that the stock markets around the world follow cyclical trends. In this paper, we study the cyclical trends using wavelet function based on various time windows on some major stock market indices. We use two methods of Daubechies and reverse bi-orthogonal wavelet methods and determine the optimal values of both methods. The results are used for Tehran stock exchange using the most recent ten years daily information as an empirical study. The details of our analysis on TEDPIX index for the last decade indicate that there are, at least, four trends of weekly, monthly, quarterly and yearly and the cycles would be expected to be repeated in future.

Data Envelopment Analysis (DEA) has been one of the most important tools on measuring the relative efficiency of different similar units such as transportation systems using terminals, airports, etc. In this study, we perform an empirical analysis on Iranian airports based on DEA methods to measure the efficiencies of various airports. One of the primary issues on many traditional DEA methods is that the data are almost always contaminated with noise. We use a DEA method which could handle the uncertainty associated with input and output data. The results of this comprehensive study show that most of the active airlines are practically inefficient and the government could significantly increase the efficiencies of the airports by setting new regulations and rules.

Designing distribution centers is normally formulated in a form of set covering where is primary objective is to minimize the number of connected facilities. However, there are other issues affecting our decision on selecting suitable distribution centers such as weather conditions, temperature, infrastructure facilities, etc. In this paper, we propose a multi-objective set covering techniques where different objectives are considered in an integrated model. The proposed model of this paper is implemented for a real-world case study of truck-industry and the results are analyzed.

When a production facility is designed, there are various parameters affecting the number machines such as production capacity and reliability. It is often a tedious task to optimize different objectives, simultaneously. The other issue is the uncertainty in many design parameters which makes it difficult to reach a desirable solution. In this paper, we present a new mathematical model with two objectives. The primary objective function is considered to be the production capacity and the secondary objective function is total reliability. The proposed model is formulated on different units of production which are connected together in serial form and for each unit, we may have various machines. The resulted model is formulated using recent advances of robust optimization and solution procedure is analyzed with some numerical examples.

This article aims to review, identify and prioritize challenge factors of the implementation of knowledge management portals for Iranian organizations. The study determines several important weakness factors affecting the implications of the knowledge management such as the weakness in organizational strategy, information overcrowd, content management, portals project management, and etc. The study also indicates that the factors have different priorities where managerial factors are in the highest priority and financial factors are in the lowest priority. We also perform factor analysis to summarize seventeen factors into six issues: Financial and information security, Technology and management, Senior management support and strategy, Acceptance, User's motivation and culture, Project management, Change management and training.

During the past three decades there have been tremendous efforts on building steel factories on economic scales. The primary question is to find an economic scale for such plants which could also meet domestic demand. In this paper, we perform an empirical survey to find out whether building small steel factories are more suitable or setting up giant steel industries to meet regional demands. The results indicate that in many countries, building small steel plants based on the recent advances of technologies not only reduces the total cost of steel production but also it could significantly reduce the unnecessary transportation cost, providing cheaper labor, etc. This would lead to better competition which would increase the productivity.