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Open AccessArticle

Advanced Methodologies for Biomass Supply Chain Planning

School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12120, Thailand
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Processes 2019, 7(10), 659; https://doi.org/10.3390/pr7100659
Received: 26 August 2019 / Revised: 19 September 2019 / Accepted: 25 September 2019 / Published: 26 September 2019
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
Renewable energy resources have received increasing attention due to environmental concerns. Biomass, one of the most important renewable energy resources, is abundant in agricultural-based countries. Typically, the biomass supply chain is large due to the huge amount of relevant data required for building the model. As a result, using a standard optimization package to determine the solution for the biomass supply chain model might not be practical. In this study, the focus is on developing and applying advanced methodologies that can be used to determine a solution for the biomass supply chain model efficiently. The decisions related to plant selection, and distribution of biomass from suppliers to plants require optimization. The methodologies considered in this research are based on stochastic programming, parameter search, and simulation-based optimization. Computational results and managerial insights based on case studies from different regions of Vietnam are provided. The results show that parameter search is suitable for small problems only, while stochastic programming is suitable for small and medium problems. For large problem, simulation-based optimization performs better when considering the quality of the solution and the run time, although, this method does not guarantee an optimal solution. It provides good solutions where the gaps to the optimal solutions are between 0.59% and 8.41%. View Full-Text
Keywords: hybrid methodology; simulation-based optimization; parameter search optimization; biomass supply chain planning; stochastic programming hybrid methodology; simulation-based optimization; parameter search optimization; biomass supply chain planning; stochastic programming
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Nguyen Duc, D.; Nananukul, N. Advanced Methodologies for Biomass Supply Chain Planning. Processes 2019, 7, 659.

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