To design a bioethanol supply chain, along with the transportation and operational costs, it is vital to consider more factors categorized into three sustainability pillars (i.e. economy, social and environment). In this paper, to develop a mathematical model for bioethanol supply chain (BSC), we propose a two-phase methodology; in the first phase, using a sustainable framework of attributes contributing to the facility location selection in the BSC network, we calculate the sustainability score of alternatives through employing the best-worst method (BWM). Then, considering the results of the multi-attribute step as the parameters of an objective function called the sustainability value function, we develop a bi-objective multi-level bioethanol supply chain model. To solve the proposed model, a Nested bi-objective Optimization Genetic Algorithm (NbOGA) is introduced in this research. Finally, we evaluate the performance of the presented BSC model and the algorithm for a real-world problem. The results show that using the proposed structure, both sustainability attributes and transportation costs are appropriately satisfied in the BSC network.@en

The purpose of this paper is to streamline the supply of corn, one of the key ingredients in the production of bioethanol. Using a comprehensive sustainable framework of criteria (including social, economic, and environmental dimensions), the potential locations of corn cultivation in Iran are examined from a multi-criteria decision analysis perspective. To this end, we need to find the importance of the relevant evaluation criteria and a ranking method to rank the potential locations. Best worst method (BWM) is used to determine the weight of the criteria presented in the framework based on the opinion of a sample of Iranian experts, after which the ‘preference ranking organization method for enrichment evaluations II’ (PROMETHEE II) is applied to ranking the different provinces of Iran. To improve the ranking results, we extend the PROMETHEE II by employing a set of piecewise linear value functions, for which the performance of alternatives with respect to the criteria calculated by the piecewise linear value functions is used to determine the amount of deviation in the first step of PROMETHEE II. The results of the hybrid methodology indicate that the presence of water, land cost and air pollution are the most important factors determining the ranking of the alternatives, and that Kordestan is the best province for corn cultivation in Iran.

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In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of specialists in Iran was asked to take part in an online questionnaire, based on best-worst method (BWM), to determine the weight of the criteria included in the proposed framework, after which a number of potential locations are evaluated on the basis of the criteria. The proposed model is evaluated under a number of settings. Using the proposed multi-criteria set-covering model, not only the utility of candidate places is evaluated by sustainability criteria but also all service applicants are covered by at least one data center with a specific coverage radius.

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In this paper, we evaluate the reasons for the failure of information systems in public universities. To that end, we start by presenting a hierarchical structure of criteria after reviewing related studies, and dividing the criteria into the categories of project management, organizational management, human-related, organizational and technical. To assess the weight of the criteria in the proposed framework, we collect the opinions of a sample of information technology experts working in different public universities in Iran, using an online questionnaire that is based on the best–worst method (BWM). By analyzing the weight of the criteria, we can reveal that misfit of information systems software (closely followed by lack of top management support and unsuccessful monitoring and measurement) has the greatest impact on the failure of information systems in the public universities of Iran. The methodology proposed in this paper can be used in other countries facing the same problem.

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Environmental problems, combined with a finite supply of fossil fuels, have made the use of renewable energy sources necessary. Biomass is a renewable source of energy that has played a very important role in energy production in recent years. Because there are a number of technologies that can be used to convert biomass into energy, it is important to select the best option. The fact that multiple options are available that need to be evaluated based on a set of decision-making criteria makes this a multicriteria decision-making problem. This paper takes the first step in proposing an evaluation framework and identifying the importance of the relevant decision-making criteria in biofuel production technology selection. To determine the importance of the selection criteria, experts were asked to respond to an online questionnaire based on the best-worst method. The results indicate that air pollution, land use change, and human expertise are the three most important criteria for selecting the best biofuel production technology in our case country, Iran.

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