An Integrated GIS–MILP Framework for Cost-Optimal Forest Biomass-to-Bioenergy Supply Chains: A Case Study in Queensland, Australia

Sam Van Holsbeeck; Mauricio Acuna; Sättar Ezzati

doi:10.3390/f16091467

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An Integrated GIS–MILP Framework for Cost-Optimal Forest Biomass-to-Bioenergy Supply Chains: A Case Study in Queensland, Australia

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An Integrated GIS–MILP Framework for Cost-Optimal Forest Biomass-to-Bioenergy Supply Chains: A Case Study in Queensland, Australia

Sam Van Holsbeeck, Mauricio Acuna and Sättar Ezzati

Forests, Vol.16(9), pp.1-19

2025

DOI: https://doi.org/10.3390/f16091467

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Abstract

forest biomass

bioenergy

facility location optimization

biomass supply chain

mixed-integer linear programming (MILP)

Renewable energy expansion requires cost-effective strategies to integrate underutilized biomass resources into energy systems. In Australia, forest residues represent a significant but largely untapped feedstock that could contribute to a more diversified energy portfolio. This study presents an integrated geospatial and optimization decision-support model designed to minimize the total cost of forest biomass-to-bioenergy supply chains through optimal facility selection and network design. The model combined geographic information systems with mixed-integer linear programming to identify the optimal candidate facility sites based on spatial constraints, biomass availability and infrastructure proximity. These inputs then informed an optimization framework that determined the number, size, and geographical distribution of bioenergy plants. The model was applied to a case study in Queensland, Australia, evaluating two strategic scenarios: (i) a biomass-driven approach that maximizes the use of forest residues; (ii) an energydriven approach that aligns facilities with regional energy consumption patterns. Results indicated that increasing the minimum facility size reduced overall costs by capitalizing on economies of scale. Biomass collection accounted for 81%–83% of total supply chain costs (excluding capital installation), emphasizing the need for logistically efficient sourcing strategies. Furthermore, the system exhibited high sensitivity to transportation distance and biomass availability; energy demands exceeding 400 MW resulted in sharply escalating transport expenses. This study provides a scalable, data-driven framework for the strategic planning of forest-based bioenergy systems. It offers actionable insights for policymakers and industry stakeholders to support the development of robust, cost-effective, and sustainable bioenergy supply chains in Australia and other regions with similar biomass resources.

Details

Title: An Integrated GIS–MILP Framework for Cost-Optimal Forest Biomass-to-Bioenergy Supply Chains: A Case Study in Queensland, Australia
Authors: Sam Van Holsbeeck - University of the Sunshine Coast, Queensland, Forest Research Institute
Mauricio Acuna - Natural Resources Institute Finland
Sättar Ezzati (Corresponding Author) - Gorgan University of Agricultural Sciences and Natural Resources
Publication details: Forests, Vol.16(9), pp.1-19
Publisher: MDPI AG
Date published: 2025
DOI: 10.3390/f16091467
ISSN: 1999-4907
Copyright note: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Data Availability: Data is contained within the article.
Grants: Australian Biomass for Bioenergy Assessment, PRJ-010376, Australian Renewable Energy Agency (Australia, Canberra) - ARENA
Organisation Unit: Forest Industries Research Centre
Language: English
Record Identifier: 991163736402621
Output Type: Journal article

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