Development of a decision support tool for optimizing the short-term logistics of forest-based biomass
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DOI: 10.1016/j.apenergy.2018.02.027
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Cited by:
- Mosayeb Dashtpeyma & Reza Ghodsi, 2021. "Forest Biomass and Bioenergy Supply Chain Resilience: A Systematic Literature Review on the Barriers and Enablers," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
- Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
- Linmao Ma & Jing Yu & Long Zhang, 2019. "An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map," Energies, MDPI, vol. 12(9), pages 1-23, April.
- Prinz, Robert & Väätäinen, Kari & Laitila, Juha & Sikanen, Lauri & Asikainen, Antti, 2019. "Analysis of energy efficiency of forest chip supply systems using discrete-event simulation," Applied Energy, Elsevier, vol. 235(C), pages 1369-1380.
- Lo, Shirleen Lee Yuen & How, Bing Shen & Leong, Wei Dong & Teng, Sin Yong & Rhamdhani, Muhammad Akbar & Sunarso, Jaka, 2021. "Techno-economic analysis for biomass supply chain: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
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Keywords
Forest biomass; Logistics optimization; Sustainability; Transshipment problem; Vehicle routing;All these keywords.
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