Enterprise resource planning (ERP) is an integrated system, which consists of various integrated applications. ERP is implemented to collect, store, manage and interpret data from different business activities, including product planning, expenses, production and/or service delivery, sales management, inventory planning, shipping and payment. The study covers the latest studies mostly on detecting factors influencing on the success of ERP implementations. The study has highlighted several factors including top management support, communication, cooperation, training and technological complexity, which were believed to be the most influential factors on development of ERP systems. In addition, several multi criteria decision making systems were used for ranking different software packages for ERP implementation. Moreover, many studies have attempted to consider mathematical methods by considering uncertainty associated with data.

Several researchers have considered similarities between Multi-Criteria Decision Making (MCDM) and Data Envelopment Analysis (DEA), as tools for solving decision making problems. As the preferences of decision- maker (DM) on alternatives are not considered in classical DEA, some researchers have tried to consider it in DEA. The UTA-STAR method is one of the techniques widely used in Multi Criteria Decision Analysis. In this technique, the preferences of decision maker on alternatives are considered and UTA-STAR tries to compute the most suitable weights for criteria and alternatives to obtain a utility function having a minimum deviation from the preferences. The goal of this paper is interpreting decision maker’s preferences in UTA-STAR method, in a new manner, using the common set of weights (CSW) in DEA.

This paper presents an integration of balanced score card (BSE) with two-stage data envelopment analysis (DEA). The proposed model of this paper uses different financial and non-financial perspectives to evaluate the performance of decision making units in different BSC stages. At each stage, a two-stage DEA method is implemented to measure the relative efficiency of decision making units and the results are monitored using the cause and effect relationships. An empirical study for a banking sector is also performed using the method developed in this paper and the results are briefly analyzed.

The interaction of Jack Bean Urease with cobalt (II) ion was studied by Isothermal Titration Calorimetry (ITC) at 300 K and 310 K in 30 mM Tris buffer, pH=7. The stability of the enzyme increases due to its binding with cobalt ions. The extended solvation model was used to reproduce the heats of Co2++JBU interaction. It was found that there is a set of 12 equivalent and noninteracting binding sites for Co2+ ions. The association equilibrium constant and the molar enthalpy of binding are 4260.76M-1, -16.5 kJmol-1 at 300 K and 3438M-1, -16 kJmol-1 at 310 K, respectively.

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.