A sustainable second-generation biodiesel supply chain network design problem under risk. (January 2017)

• Record Type: Journal Article
• Authors: Babazadeh, Reza; Razmi, Jafar; Pishvaee, Mir Saman; Rabbani, Masoud
• Is Part Of: Omega. Volume 66:Part B(2017:Jan.)
• Page Start: 258
• Page End: 277
• Publication Date: 2017-01
• Subjects: Sustainable development -- Second-generation biodiesel supply chain -- Non-edible feedstock -- Possibilistic programming -- Multi-objective optimization; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2015.12.010
• Languages: English
• ISSNs: 0305-0483

Abstract

Abstract: This paper presents a multi-objective possibilistic programming model to design a second-generation biodiesel supply chain network under risk. The proposed model minimizes the total costs of biodiesel supply chain from feedstock supply centers to customer centers besides minimizing the environmental impact (EI) of all involved processes under a well-to-wheel perspective. Non-edible feedstocks are considered for biodiesel production. Variable cultivation cost of non-edible feedstock is assumed to be non-linear and dependent upon the amount of cultivated area. New formulation of possibilistic programming method is developed which is able to minimize the total mean and risk values of problems with possibilistic-based uncertainty. To solve the proposed multi-objective model, a hybrid solution approach based on flexible lexicographic and augmented ɛ-constraint methods is proposed which is capable to find appropriate efficient solutions from the Pareto-optimal set. The performance of the proposed possibilistic programming method as well as the developed solution approach are evaluated and validated through conducting a real case study in Iran. The outcome of this study demonstrates that high investment cost is required for improving the environmental impact and risk of sustainable biodiesel supply chain network design under risk. Decision maker preferences are required for suitable trade-off among total costs, risk values and environmental impact. Highlights: Developing a multi-objective possibilistic programming model for designing a second-generation biodiesel supply chain network considering total cost and environmental impact minimization. Presenting a new formulation of possibilistic programming method which is able to minimize the total mean and risk values of possibilistic-based uncertain problems. Proposing a hybrid solution approach based on flexible lexicographic and augmented ɛ-constraint methods to find Pareto-optimal solutions. Conducting a real-life case study in Iran to evaluate the performance and efficiency of the proposed model and solution approaches.