An integrated model of land-use trade-offs and expanding agricultural processing centres

A. Nazari, S. Penazzi, A. T. Ernst, S. Dunstall, B. Bryan, J. Connor, M. Nolan

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Abstract

Climate change and demand for greener energy alternatives are putting increased pressure on the use of agricultural land for not just for food and fibre production but also biofuels, carbon sequestration,biodiversity and other non-traditional uses. A key question is how this competition might impact on not only future land use but also on the composition of the supply chains that process the products of the land. In this paper we address a major part of this question by considering the location of processing centres alongside land use change in an integrated optimisation model. CSIRO has previously developed a model of land use trade-offs that considers the possible evolution of agricultural land areas in Australia over the next 40 years. This can be modelled as a large scale multi-stage linear programming problem. Here we consider in addition the construction of some processing centres for bio-fuel, bio-energy, livestock facilities and so forth, which introduces a new combinatorial aspect to the model. The decisions of land use and the location of processing centres are interlinked, because transport costs based on distances are often instrumental in determining the economic viability of some of the land uses and conversely economies of scale are necessary to justify investment in processing plants.

In this paper we introduce a model containing both problems of a land allocation and a facility location simultaneously which results in a large scale mixed integer linear programming (MILP) problem and therefore is computationally difficult to solve. We suggest an algorithm to solve the problem which utilises some decomposition techniques including aggregation and disaggregation, column generation and a concept of clustering. Furthermore, some numerical results are provide to empirically show the computational feasibility of the suggested solution methodology.
Original languageEnglish
Title of host publicationProceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015
EditorsTony Weber, Malcolm McPhee, Robert Anderssen
Place of PublicationQld Australia
PublisherModelling and Simulation Society of Australia and New Zealand (MSSANZ)
Pages1219-1225
Number of pages7
ISBN (Electronic)9780987214355
Publication statusPublished - 2015
Externally publishedYes
EventInternational Congress on Modelling and Simulation 2015: Partnering with industry and the community for innovation and impact through modelling - Gold Coast Convention and Exhibition Centre, Broadbeach, Australia
Duration: 29 Nov 20154 Dec 2015
Conference number: 21st
https://www.mssanz.org.au/modsim2015/

Conference

ConferenceInternational Congress on Modelling and Simulation 2015
Abbreviated titleMODSIM2015
Country/TerritoryAustralia
CityBroadbeach
Period29/11/154/12/15
OtherThe 21st International Congress on Modelling and Simulation (MODSIM2015) was held at the Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia from Sunday 29 November to Friday 4 December 2015.

It was held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium (DORS 2015).

The theme for this event was Partnering with industry and the community for innovation and impact through modelling.

Papers from these proceedings should be cited using this format:

Walmsley, B.J., Oddy, V.H., Gudex, B.W., Mayer, D.G. and McPhee, M.J. (2015). Transformation of the BeefSpecs fat calculator: Addressing eating quality and production efficiency with on-farm decision making. In Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 490–496. ISBN: 978-0-9872143-5-5. www.mssanz.org.au/modsim2015/B4/walmsley.pdf
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Keywords

  • Mixed integer linear programming
  • Land use management
  • Facility location

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