Industrial Management Journal
Year:2015 | Volume:7 | Issue:1 |Papers Count:10

Gasoline is the most important energy product in the passenger transportation sector in Iran. Gasoline demand survey has a high priority in Iran because of its ever-increasing consumption. The most important challenges for this purpose are uncertainties resulting from structural failure of economy, changing of policies and lack of accurate data. This research aims to specify the variables explaining the gasoline demand in Iran and to estimate gasoline demand by using the statistical and fuzzy regression models over the period 1981-2007. Finally, the models were compared using standard criteria. The results indicate that both methods have enough accuracy for estimating and forecasting gasoline demand. In addition, there is a significant relationship between gasoline price, car per capita and trend as explanatory variables of gasoline demand per capita.

A vast number of organizational projects as well as complexity of decision making process can cause particular challenges for project management and its leadership. In order to use organization assets and opportunities efficiently, it is necessary that manager implement a comprehensive multidimensional project portfolio management system that considers economic, social and technical details of the projects. Resource constraint compels managers to select operational proposal projects. Thus managers can maximize organizational utility due to project portfolio’s resource constraint. This study considers the interactive effects of project portfolio evaluation and sharing organizational project resources with respect to its evaluation and choice of the projects. In this two-step model, first a branch and bound algorithm with resource interaction was utilized to screen maximal portfolio and, in the next step, each portfolio was evaluated based on artificial neural networks to rank the end project portfolios. Also, the ANN scores are strongly correlated with the DEA and COLS efficiency scores.

Since the analysis of complex services systems by using mathematical modeling techniques, with considering the random patterns prevailing in them, is so difficult or probably impossible, improvement guidelines are often followed based on the experts' experiences using qualitative methods. In the present paper, by employing a discrete event computer simulation methodology, criminal trial system has been quantitatively analyzed in a selected court in Iran and appropriate operational strategies to improve a couple of system performance indicators have been provided using sophisticated statistical tools such as design of experiments, hypothesis testing, regression analysis, sensitivity analysis and multi-objective optimization. Simulation results show possibility of a 27% reduction in average responding time on penal claims and simultaneously 80% reduction on repeated referral rate. Also, in order to examine analytical details, computer simulation model was validated using hypothesis testing method on a few dummy response variables.

This research provides an optimization tool for use by supply chain managers in the design and operation of manufacturing- distribution networks under uncertain demand conditions. The problem under consideration consists of determining the supply chain infrastructure; raw material purchases, shipments, and inventories; and finished product production quantities, inventories, and shipments needed to achieve maximum profit while fulfilling demand and minimizing profit variability and unsatisfied demand. This research presented a model to supply chain infrastructure design. In this research, a multi-period, multi objective mixed integer robust optimization formulation of the strategic model is presented to account for the probabilistic demand data. For this purpose, numerical examples are presented and solved by LINDO software.

The current research aims to study the industrial and technological concerns within transfer process of high-tech regarding the technology readiness levels (TRLs). The importance of the subject is emphasized because different TRLs have special considerations and the risks of high-tech transfer can be reduced considering them. The main goal of this study is to identify and rank the industrial and technological concerns in transfer of high-tech at various levels of technology readiness. The study is applied-type and the data were collected using mixed method. Research findings show that 32 elements as seven aspects of industry and technology considerations influence the transfer of high-techs. The influence of these factors varies at various TRLs, such that as we move toward higher readiness levels (1 to 9), the influence of industry considerations is more than that of technology considerations. It is highly recommended for companies active in the field of high-techs transfer to take into account industry and technology considerations and their influences on different TRLs.

The most important issues that should be considered in studying disaster management include temporary settlement of injured population, supplying relief commodities, designing an appropriate communication infrastructure for communication during disaster. For this purpose, in this paper a model has been proposed for locating shelters, warehouses of relief commodities, and also telecom towers, whereas warehouses of relief commodities and telecom towers have been considered as the telecom-relief center for reducing costs and improving services. The problem has been modeled as a nonlinear and bi-objective model, while for solving the problem normalization method and linearization approach have been applied. With respect to significance of unstable conditions and dynamic environment in natural disasters, the model has been considered under uncertainty and possibilistic programming approach is used to cope with this issue. The proposed model is implemented in the flood disaster case study of Tehran and the obtained results show that the optimal location of the facility can help the decision makers of disaster management in this area to increase service provision during disaster.

Compared to industrial companies, we have neither enough related literature nor available researches concerning the issue of evaluating the supply chain management as well as supply chain performance. Therefore, the current article aims to identify and prioritize measures of evaluating the performance of services supply chain. Thus, we first review the related text and define the processes of supply chain. Also, we explain the measures of evaluating the mentioned processes; finally, we sort the measures in accordance with Score and Seroquel models and we design the respected decision tree. The prepared questionnaires were distributed among the managers who are considered as the experts in service industries. Then, after gathering the completed questioners, we used fuzzy AHP for prioritizing and sorting the measures. The results show that the reliability indicator has the highest importance while intangibility has the least importance in supply chain services.

In this paper, a model for evaluating and ranking constructive projects will be presented. This model is based on six key criteria and a conceptual framework. These main evaluation criteria include: good history, equipment and machinery, management and technical staff, economic - financial skills and experience, and scientific and technical capabilities. These criteria and their weights were derived from previous studies. The vagueness of the linguistic terms in the evaluation process required employment of fuzzy numbers. Then, the fuzzy PROMETHEE method was used for ranking the projects. To test the model and as a case study, contractors of Mehr housing projects in Hashtgerd new Town were ranked. This model can be used for evaluating and ranking contractors for various construction projects.