JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES
Year:2011 | Volume:8 | Issue:21|Papers Count:9

Simultaneous with port's development and complexity III transportation processes, a number of problems have occurred in global supply chain. Nowadays, new technologies are used as a flexible solution to control quality of services and manage port's processes. One of the most effective existing technologies that can be used for container transportation is RFID technology. The most important benefit of RFID technology is the automation of processes through providing decision support systems based on real time and accurate data.This study follows an efficient RFID-Based model to improve port's container transportation. According to Literature review and available academic models, the port's RFID system cycle has been designed and a model has been proposed. This model has used the internal experience and the result of the initial site has been surveyed. By understanding the conceptual variables in the model and analysis of questionnaire's data and obtaining RFID and port expert's ideas, the final model has been presented.According to the study, the proposed model is believed to be efficient for Bushehr port's and has positive effect on security, speeding, Transparency and container's processes visibility and can be used as a pattern for other ports.

Data Envelopment Analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer Decision Making Units (DMUs) with multiple input and outputs. However, some problems have also appeared as the applications of DEA advance. One of inter-related problems that has long been known is the lack of discrimination power. The lack of discriminating power problem occurs when the number of DMUs under evaluation is not large enough compared to the total number of inputs-outputs. In this situation, classical DEA models often yield solutions that identify too many DMUs as efficient. In this study the base of the modeling is technique Data Envelopment Analysis But in order to increase accuracy in assessing banks performance and identify the inefficiency and efficiency units, designing a model that combines data envelopment analysis and Goal Programming and also performance of the banks are measured in this perspective. The results of this study showed the higher ability of the presented model toward the basic models to separate the banking units.

Shortest-path problem is one of the well-known optimization problems that has been studied by many scientists in recent years.Applications of this problem such as transportation and communication are generally solved by Dijkstra's Algorithm (Labeling). In this paper, two separate scientific fields, electronics and operation research have been linked to each other and a new algorithm has been created for to find the optimization solution of a shortest path problem by using electric networks and rules. The proposed algorithm can solve the shortest-path problem in directed graphs and no order ones, and also can solve the longest path problems in directed graphs.In this algorithm, electrical network are used in a way that the resistance value of each branch is equal to each edge weights in the shortest-path problems. Then with using Ohm Law and Kirchhaffs Voltage Law (KVL), the current in each circuit cycle is calculated.Then the branches that contain the most passing current are specified, and according to Ohm's Law, have the lowest resistance or weight.Thus, the shortest path in the network is achieved. Advantage of this algorithm is faster convergence to the answer and less computing time than the conventional method, specially in networks with more nods.The mentioned algorithm has been described for three examples.

Nowadays, inventory management has a significant importance in supply chain. In supply chain management literature, inventory control and minimizing inventory-related cost are a main challenges confronting the managers. One of the issues attracting the attention of most researchers is determining the level of safety stock in such a way that enables us to reach appropriate fill rate. In this paper, a non-linear model to determine the level of safety stock in different components of supply chain is presented with the aim of minimizing the safety stock-related cost.

In today's business world, agility is considered as one of the most important characteristics in competitive industries. Hence, this study presents a new approach toward promoting organizational agility in companies and institutions. The proposed approach is based on the Quality Function Deployment (QFD) technique, and, is accomplished by constructing two House of Quality (HOQ) Sequentially. As the first step, the most important competitive bases related to desired industry, should be identified.The second step is allocated to identify and strengthen those agile attributes which are needed for the company in order to achieve the competitive bases. Finally, as the third Step, proper agile enablers that are suitable tools to achieve the mentioned agile attributes, identified and being exploited.As a result, the organization can attain market competitive bases relying on a set of appropriate agile enablers related to its specialized field of activity.In this paper, the whole scaffold exploits fuzzy logic to translate linguistics judgements of experts into numerical values.Eventually, an illustrative example, grounded on data available in literature, is presented and discussed to investigate the proposed approach analytically.

Supply chain is a network of independent organizations that cooperate with each other, in order to control, manage and improve material and information flow from suppliers to final consumers to meet customer satisfaction. In Industry, especially industries that are moving towards the longer supply chain, the issue of supply chain risk management is important.The risk management process focuses on the identification of risks and reduction of theirs adverse effects. Risk management process in supply chain includes four-phase identification, assessment, control or management and tracking of risky events. The aim of risk assessment is risk measurement based on various attributes. A key part of this process is risk rating, in this article first, with study of multi criteria decision making, it was tried to recognize the appropriate model for ranking of risk factors in order to determine their priority and allocate resources to deal with each of them. More, the field of information technology in small and medium enterprises was studied and after recognizing of risk factors of field of information technology in small and medium enterprises, Electre, Topsis and Taxonomy techniques to rank these factors were used.More and also with calculating the Spearman correlation coefficient for detecting convergence of ratings, using the mean method, the final ranking risk factors in the supply chain field were acquired.

Some real world problems include determining optimum values of input variables in order to obtain the desired levels of output variable (response surface variable). One of the applicable techniques which is used for modeling and solving such problems is Response Surface Methodology (RSM). In this paper, the effect of three controllable input factors: temperature, the density of sodium cyanid, and ampere on the determined response surface level i.e. the thickness of the electroplating cover of a hook screw is checked by Design Of Experiments (DOE). After the execution of experiments and the recognition of effective factors, according to the application of response surface methodology, the relationship between the variables of effective input factors and the response surface variable is determined with the help of nonlinear regression model. Then, the optimum value of each variable in nonlinear model is obtained by goal programming method.

Price bubble is a phenomenon in which the assets prices go up considerably. The research shows that bubbles have Non-Linear characteristic, and common methods of stock valuation such as Discounted cash flow models and relative models, usually are unable to evaluate stock values. Common and Non-Systemic approach has linear and cascading perspective for considering phenomenon but systemic approach has Non-Linear approach. In this research, stock prices bubble in auto industry is considered by systemic thinking and is modeled by system dynamics approach. Two influencing factors are tested in the paper: belief changes speed and block purchasing. Both factors make the stock more volatile. So, the higher the speed and the larger the amount, the greater the stock volatility. Also, block transaction causes sentimental atmosphere among investors and pushes retail investors.

For a network with cycle, where at least one cycle exists, the Floyd-War shall algorithm is probably the most used algorithm to determine the least cost path between every pair of nodes on this network, i.e. the solution for the shortest path problem with cycle.In this paper, a new algorithm for this problem which requires less computational effort than the Floyd- War shall algorithm has been developed Furthermore, it can be shown that the basis of our algorithm is much easier to be learnt and understood which might be an advantage for educational purposes. A small example validates our algorithm and shows its implementation.