This paper proposes an improved critical chain method with fuzzy approach to schedule projects under uncertainty. Utilizing fuzzy numbers can be wise because of the natural uncertainty in estimation of required work to accomplish the project tasks. To minimize the project duration as an objective taking into account resource limitations and other constrains, a Resource Constraint Project Scheduling Problem model (RCPSP) is adopted. The output of this model determines the project schedule. Then, a new buffer sizing approach based on the square root of the sum of the squares (SSQ) method is introduced which is modified by coefficients to overcome the schedule risk more efficiently. As a result, a project buffer is added to the end of the project schedule and is used if necessary. The methodology can be used as a control procedure.

With the heightened awareness of global environmental issues of greenhouse gas emissions by fossil fuels as non-renewable energy resources, the application of renewable energies (REs) has emerged as one of the most significant policies in most of the countries throughout the world. Although Iran is blessed with high potential of RE resources such as solar, wind, and geothermal, development of such resources, however, has been neglected due to the various reasons. Considering the long time needed to develop and deploy RE resources, a long-term planning is required in this area. Therefore, applying the scenario planning method, this research develops four scenarios in Iran's 2025 vision, through a combination of the changes in energy consumption and RE generation: green path, standardization, fossil energy, and non-targeted subsidy. Developed scenarios are then compared with the government plan for utilizing REs in 10 % of total electric power generation in a 20-year vision. Results indicate that standardization and fossil energy are the most probable scenarios. Green path is the most optimistic scenario for the country, suggesting the goal of producing 10 % of total electricity share through REs could be achievable by 2025. And the non-targeted subsidy is the most pessimistic and unexpected scenario for the country.

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Effective design of biodiesel supply chain network can reduce many of its high production costs. There are various uncertain parameters in real world that if ignored may greatly affect the optimal configuration of the designed biodiesel supply chain. Scenario planning is a powerful tool which can help the decision makers for long-term planning under uncertainties. Therefore, in this paper, a scenario-based robust optimization model is presented for designing the biodiesel supply chain networks under uncertainties. Some of the parameters including demand, supply, costs, and environmental impacts have uncertain nature. For the first time, in this study, the values of these uncertain parameters are estimated by a proposed scenario-planning method. The presented scenario-planning approach is based on cross-impact analysis and visualization methods. Non-edible sources such as Jatropha, Norouzak, and waste cooking oil are considered as raw materials of biodiesel production, and for the first time Norouzak has been used as one of the sources in designing biodiesel supply chain. In addition, an environmental constraint is considered and the environmental impacts of all processes are obtained by Eco-indicator 99 method. The presented model can determine the number, location, and capacity of the facilities. The proposed model is implemented in a real case study in Iran for a 7-year planning horizon. The results show the effectiveness of the presented approach in designing the biodiesel supply chain networks under uncertainties.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

In our country, most of the rivers located in dry and