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The influence of Hazardous Materials on different kind of human aspects motivate scholars to increase their attention for decreasing negative impacts of them to human life. In this concern, this paper addresses a decision structure to transfer the hazardous materials to the safe location in the industries logistic system. To reach this goal, we present a new mathematical modelling problem in which location routing problem of hazardous material is addressed. To cope imprecise risk in a practical way, we define it to three kinds in the fuzzy environment including accident risk, population risk, and the bio-environmental risk. To obtain optimal results, three well-known multi-objective evolutionary algorithms (MOEAs) including Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm II (SPEA-II) and Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) are presented for solving ten test problems. In this case, this novelty of the model is discussed, firstly, and then proposed algorithms are compared with respect to obtained results. The results of this paper show that Non-dominated Sorting Genetic Algorithm II (NSGA-II) has superior performance in terms of metrics, and Strength Pareto Evolutionary Algorithm II (SPEA-II) beats other multi-objective evolutionary algorithms in terms of obtained number of individuals in final Pareto solutions. [ABSTRACT FROM AUTHOR]

This paper is based on a review of 183 detailed, major accident investigation and analysis reports related to the handling, processing and storage of hydrocarbons and hazardous chemicals over a decade from 2000 to 2011. The reports cover technical, human and organizational factors. In this paper, the Work and Accident Process (WAP) classification scheme is applied to the accident reports with the intention of investigating to what extent maintenance has been a cause of major accidents and what maintenance-related causes have been the most frequent. The main objectives are: (1) to present more current overall statistics of maintenance-related major accidents, (2) to investigate the trend of maintenance-related major accidents over time, and (3) to investigate which maintenance-related major accident causes are the most frequent, requiring the most attention in the drive for improvement. The paper presents statistical analysis and interpretation of maintenance-related major accidents' moving averages as well as data related to the types of facility, hazardous substances, major accidents and causes. This is based on a thorough review of accident investigation reports. It is found that out of 183 major accidents in the US and Europe, maintenance was linked to 80 (44%) and that the accident trend is decreasing. The results also show that "lack of barrier maintenance" (50%), "deficient design, organization and resource management" (85%) and "deficient planning/scheduling/fault diagnosis" (69%) are the most frequent causes in terms of the active accident process, the latent accident process and the work process respectively. [ABSTRACT FROM AUTHOR]

Abstract: The storage of dangerous substances is a high risk procedure: a historical analysis revealed that 17% of the major accidents associated with the chemical industry are related to this process. When a storage facility is designed, the investment in safety is not always optimal. The safety measures that are applied are sometimes redundant or ill-maintained. One way to improve safety in a storage facility would be to take advantage of the fact that dividing the mass of dangerous substance results in less catastrophic accidents. In this paper, we present a new method for optimizing the design of storage plants and minimizing the risk by calculating the ideal number of tanks and improving the way in which money is invested in safety. This is achieved by redefining how to estimate risk and by applying the principles of mathematical optimization to quantitative risk analysis. The method is explained step by step. We also present two case studies and a validation of the method using risk analysis software and iso-risk curves. [Copyright &y& Elsevier]