Abstract

Biomass logistics comprise of inter-dependent operations related to harvesting and collection, storage, pre-processing, and transportation. Its high cost represents one of the barriers in widespread use of biomass for energy and fuel production. Therefore, improving and optimizing biomass logistics are essential in overcoming this barrier. Biomass logistics was reviewed in a previous study that aimed at categorizing logistics operations, but the inherent issues and complexities, and how they were incorporated in mathematical models were not discussed in detail. The objective of this paper is to review the important features of biomass logistics operations, discuss how they were incorporated in mathematical optimization models, and explain the new trends in biomass logistics optimization. Differences between the models dealing with forest-based and agriculture-based biomass are highlighted. Important features incorporated in logistics models include demand-driven and supply-driven collection, collection of biomass in different forms, storage at intermediate facilities, biomass quality deterioration, inter-modal distribution for long-distance transportation, operational level transportation planning, and planning the pre-processing of biomass. Recent trends in biomass logistics models include the consideration of scattered availability of biomass across supply areas, uncertainties in biomass supply, integration with GIS, emissions from logistics operations, and traffic congestion due to biomass transportation. Most of the literature on biomass logistics focused on medium-term planning, while that for short-term planning is still in its infancy. The current biomass logistics models focused mainly on economic objectives, while environmental concerns related to emissions from logistics activities received limited attention. The trade-off between environmental and economic aspects of biomass logistics operations have not been investigated. Social aspects such as increase in traffic congestion due to biomass transportation received limited attention in the literature. Most of the previous models were tested on hypothetical cases, while developing suitable models to address practical issues in real case studies would be valuable.

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