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Given the fact that during the recent years the majority of buildings in Iran have been constructed either on steel or concrete frames, it is essential to investigate the environmental impacts of materials used in such constructions. For this purpose, two multi-story residential buildings in Tehran with a similar function have been considered in this study. One building was constructed with a steel frame and the other was constructed with a concrete frame. Using the life cycle assessment tool, a complete analysis of all the stages of a building’s life cycle from raw material acquisition to demolition and recycling of wastes was carried out. In this research, the environmental impacts included global warming potential in 100 years, acidification, eutrophication potential, human toxicity (cancer and non-cancer effects), resource depletion (water and mineral), climate change, fossil fuel consumption, air acidification and biotoxicity. It could be concluded from the results that the total pollution of the concrete frame in all eleven aforementioned impact factors was almost 219,000 tonnes higher than that of the steel frame. Moreover, based on the results, the concrete frame had poorer performance in all but one impact factor. With respect to global warming potential, the findings indicated there were two types of organic and non-organic gases that had an impact on global warming. Among non-organic emissions, CO2 had the biggest contribution to global warming potential, while among organic emissions, methane was the top contributor. These findings suggest the use of steel frames in the building industry in Iran to prevent further environmental damage; however, in the future, more research studies in this area are needed to completely investigate all aspects of decision on the choice of building frames, including economic and social aspects.

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The stochastic location-allocation p-hub median problems are related to long-term decisions made in risky situations. Due to the importance of this type of problems in real-world applications, the authors were motivated to propose an approach to obtain more reliable policies in stochastic environments considering the decision makers' preferences. Therefore, a systematic approach to make robust decisions for the single location-allocation p-hub median problem based on mean-variance theory and twostage stochastic programming was developed. The approach involves three main phases, namely location modeling, risk modeling, and decision making, each including several steps. In the first phase, the pertinent location-allocation model of the problem is developed in the form of a two-stage stochastic model based on its deterministic version. A risk measure, based on total cost function and mean-variance theory, is derived in the second phase. Furthermore, two heterogeneous terms of the risk measure have been normalized and an innovative procedure has been proposed to significantly improve the calculation efficiency. In the third phase, the Pareto solution is obtained, the frontier curve is depicted to determine the decision maker's risk aversion coefficient, and a robust policy is obtained through optimization based on decision makers' preferences. Finally, a case study of an automobile part distribution system with stochastic demand is described to further illustrate our risk management and analysis approach.

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