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Forest biomass (FB) could supply more of Australia’s energy needs, but delivered costs must be reduced for it to be a viable energy source. Operational planning is critical to reducing delivered costs as it determines actual activities, though few operational FB supply chain (FBSC) planning tools have been published. This paper presents a “proof-of-concept” operational FBSC decision support system (DSS) to schedule FB deliveries for eight weeks from roadside storage for the least cost, taking in account moisture content changes. Four mathematical models are compared, solving a linear formulation of the FB delivery problem in terms of solution speed and delivered cost, and the practicality of implementing the solutions. The best performing model was a Greedy algorithm as it produced solutions not significantly different from those of the tested linear programming solver and was readily modified to significantly improve solution implementation through the addition of a non-linear element. FBSC planning tools typically assume accurate knowledge of stored FB quantities and that little or no rainfall occurs during storage. In practice, stored FB quantity estimates can be inaccurate due to variation in the bulk density of the piles. Improving these estimates is a critical area for future research. This study found that simulated rainfall with &lt;20 mm during the first week of the scheduled period did not significantly effect delivered costs.

Optimizing Operational-Level Forest Biomass Logistic Costs for Storage, Chipping and Transportation through Roadside Drying