Transportation of hazardous materials in Iran: A strategic approach for decreasing accidents

“Hazardous materials” refer to those substances that seriously endanger human lives and/or the environment. The transportation of these materials will be inevitable in the increasingly industrialized economy of Iran. Nonetheless, numerous deadly accidents caused by the movement of these materials necessitate the design and implementation of preventive plans on several levels. This article looks into the present condition of transportation of hazardous materials in Iran and the resulting accidents. Optimal condition for the general transportation system of hazardous materials is delineated with due focus on transportation risk as the main parameter. Strategies for reaching the optimal condition are laid out and the impacts of these strategies on the reduction of accidents are analyzed. First published online: 27 Oct 201

Developing strategies to reduce the risk of hazardous materials transportation in Iran using the method of fuzzy swot analysis

An increase in hazardous materials transportation in Iran along with the industrial development and increase of resulted deadly accidents necessitate the development and implementation of some strategies to reduce these incidents. SWOT analysis is an efficient method for developing strategies, however, its structural problems, including a lack of prioritizing internal and external factors and inability to consider two sided factors reducing its performance in the situations where the number of internal and external factors affecting the risk of hazardous materials is relatively high and some factors are two sided in nature are presented in the article. Fuzzy SWOT analysis is a method the use of which helps with solving these problems and is the issue of employing an effective methodology. Also, the article compares the resulted strategies of the fuzzy method with the strategies developed following SWOT in order to show the relative supremacy of the new method. First published online: 27 Oct 201

Designing Stochastic Cell Formation Problem Using Queuing Theory

This paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. In this research, cells are defined as a queue system which will be optimized via queuing theory. In this queue system, each machine is assumed as a server and each part as a customer. The grouping of machines and parts are optimized based on the mean waiting time. For solving exactly, the proposed model is linearized. Since the cell formation problem is NP-Hard, two algorithms based on genetic and modified particle swarm optimization (MPSO) algorithms are developed to solve the problem. For generating of initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Also, full factorial and Taguchi methods are used to set the crucial parameters in the solutions procedures. Numerical experiments are used to evaluate the performance of the proposed algorithms. The results of the study show that the proposed algorithms are capable of generating better quality solutions in much less time. Finally, a statistical method is used which confirmed that the MPSO algorithm generates higher quality solutions in comparison with the genetic algorithm (GA)