Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective. (March 2016)

• Record Type: Journal Article
• Authors: Ba, Birome Holo; Prins, Christian; Prodhon, Caroline
• Is Part Of: Renewable energy. Volume 87:Part 2(2016)
• Page Start: 977
• Page End: 989
• Publication Date: 2016-03
• Subjects: Biomass -- Logistics -- Supply chain -- Modeling -- Optimization -- Bioenergy; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.07.045
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The production of biofuels, bioenergy and chemical intermediates from biomass is a promising solution to reduce the consumption of fossil fuels and greenhouse gas emissions. While a significant research effort has been devoted to biomass production and conversion processes, the importance of logistics was detected more recently. Indeed, efficient supply chains are essential to provide conversion facilities with sufficient quantities of quality biomass at reasonable prices. As large territories and hundreds of biomass producers are involved, quantitative models are very useful to evaluate and optimize the resources required, the associated costs, the energy consumptions and the environmental impacts. This article surveys the recent research on models for biomass supply chains, from an Operations Research perspective. 124 references, including 72 published since 2010, have been analyzed to present the structures and the activities of these chains, a typology of decisions in three levels (strategic, tactical and operational), and a review of models based either on performance evaluation techniques (e.g., simulation) or mathematical optimization. A conclusion underlines the contributions and shortcomings of current research and suggests possible directions. Highlights: Recent models to design, evaluate and optimize biomass supply chains are surveyed. 124 references are analyzed, including 72 published since 2010. Both optimization and performance evaluation approaches like simulation are covered. Stochastic optimization and multi-objective models are included. Solution methods (commercial solvers or specific algorithms) are also mentioned.