An analytical and numerical solution is developed for a transient heat conduction equation in which a plane slab is heated by a bimodal distribution beam over the upper surface. In laser heat treatment of steel few methods are used to produce a wider and nearly uniform average irradiance profile. This may be achieved by a bimodal (TEM11) shaped laser beam. In this paper, Green function method is employed to derive an analytical solution for thermal field distribution induced by laser forming process. Then 3-D finite element modeling of a slab in the ANSYS code is used to model the thermal field of laser forming with bimodal beam distribution. The results show that bimodal beam is useful for obtaining a uniform heat intensity distribution.

The primary objective of this research is to investigate the relationship between tax avoidance, income and cash held in companies listed on the Tehran Stock Exchange from 2009 to 2013. In this regard, avoidance of paying taxes is independent variables and criteria for evaluating financial performance; namely return on assets, return on average equities, economic value added, market value added, and the ratio of free cash flow are considered as dependent variables. Firm size and financial leverage are also considered as control variables. In general, the statistical method used in this research is correlation and regression. The results of the research showed that there was a significant and reverse relationship between avoidance of paying taxes and performance evaluation criteria, cash held.

This paper presents an empirical investigation to determine important business intelligence factors influencing on development of export activities. The study selects a sample of business developers who were involved in export activities in city of Tehran, Iran. Cronbach alpha based on standardized items was calculated as 0.882, which is well above the minimum desirable level. In addition, Bartlett & apos; s test of Sphericity yields a Chi-Square value of 3242.82 (df = 861, Sig. = 0.000). Using principle component analysis, the study has determined four factors including competitive position, organizational resources, efficient system and customer orientation influencing on development of export activities.

Having a supply chain is an unavoidable fact and all companies should focus on if they wish to survive in the competitive business world. This paper ranks criteria influencing on behavior of a medicine manufacturer agent when its goal is to select the supplier agents to interact with across a pharmaceutical agent based supply chain. The pharmaceutical industry is important for countries due to the distinguished role of health in societies and Iran is not an exception too. Besides, the industry in this country is encountered with some limitations because of the situation imposed by sanctions. In this study, first, ten criteria were selected based on expert’s opinions, two categories of quantitative as well as qualitative criteria were chosen for ranking the criteria and then TOPSIS and PROMETHEE ? methods were applied to rank the criteria. According to the results of this survey, qualitative criteria were determined as important factors influencing on supplier selection.

In supply chain management, supplier performance is evaluated based on several criteria. In this paper, a fuzzy multi-objective mathematical programming model is presented to consider different qualitative and quantitative factors to choose appropriate suppliers and the optimal order quantity allocated to them. The proposed study uses analytical hierarchy process to rank different suppliers and a fuzzy multi-objective mathematical programming is presented to choose the best suppliers. The study uses NSGAII to solve the resulted problem and the model is analysed using some sample results under various circumstances. The study considers different Pareto solution set obtained by TOPSIS ranking algorithm, and eventually determines the best possible solutions.

Inventory planning for the pre- and post-disaster phases of disaster relief lifecycle is a challenging problem associated with the humanitarian relief supply chains. In this work, two mathematical models are presented encompassing the whole disaster relief lifecycle. By accounting for holding costs of perishable supplies, a two-stage stochastic programming model is first developed by which the inventory prepositioning locations, inventory levels, and short-term distribution quantities are determined. For the recovery phase, this research adapts the well-known continuous review (Q, r) inventory model for relief warehouses while accounting for the inherent epistemic uncertainty in the required data by using the fuzzy programming. A case study of Iranian Red Cross is also provided to illustrate the applicability of the first model and to demonstrate how it supports the two first phases of disaster lifecycle. Additionally, a numerical example is presented to demonstrate the applicability of the (Q, r) model for the recovery phase. Lastly, the impact of penalty costs on the solutions is discussed.

Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers.

Performance measurement plays essential role on improving the performance of business units and their efficiencies. During the past few years, there have been tremendous development in banking systems and the primary focus of many managers is to improve the quality of services for market retention. Performance measurement in banking industry is normally involved with various qualitative as well as quantitative criteria, which leads to the implementation of multiple criteria decision making techniques. This paper presents a hybrid grey relational analysis and K-means to cluster and measure the performance of banking system. The proposed study uses different criteria, clusters banks into various segments and ranks 43 different banks in city of Semnan, Iran.

Mining is one of the most important sectors in most countries. It produces raw material for other sectors such as industry, agriculture, etc. Therefore, governments always seek the solutions to prevent or at least reduce the risk of mining industry to minimize the waste of time and resource. One of the most popular risk in mining industry that should be clearly assessed is supply chain. There is a variety of methods to evaluate and classify risks. Fuzzy set is one of the most appropriate methods to categorize and evaluate risks, because this method is able to take into account the uncertainty involved in the process of risk assessment. In this article, fuzzy inference system is applied to evaluate and assess the supply chain risk of the Iranian mining industry. This research shows that the proposed model had a high accuracy and efficiency for assessing the risk of mining industry.

Today, the world facing with huge flood of data and the recent advances in computer technology have provided the capability to process significant amount of data. On the other hand, analyzing the information requires resources that most institutions do not have, independently. To handle such circumstances, grid computing has emerged as an important research area where the calculation of distributed computing and clustering are different. In this study, we propose a grid computing architecture as a set of protocols that use the cumulative knowledge of computers, networks, databases and scientific instruments based on the implementation of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. The results of the implementation of the proposed algorithm on grid systems indicate the superiority of the proposed approach in terms of validation criteria scheduling algorithms, such as task completion time and the performance compared with some alternative method.