A framework for optimising capital investment and operations in livestock logistics
Andrew Higgins A G , Ian Watson B , Chris Chilcott C , Mingwei Zhou F , Rodolfo García-Flores D , Sandra Eady E , Stephen McFallan A , Di Prestwidge A and Luis Laredo AA CSIRO Ecosystem Sciences, GPO Box 2583, Brisbane, Qld 4001, Australia.
B CSIRO Ecosystem Sciences, PMB Aitkenvale, Townsville, Qld 4850, Australia.
C Queensland Government – Department of Agriculture, Forestry and Fisheries, 80 Anne Street, Brisbane, Qld 4001, Australia.
D CSIRO Mathematics, Informatics and Statistics, Normanby Road, Clayton, Vic. 3168, Australia.
E CSIRO Animal, Food and Health Sciences, Locked Bag, Armidale, NSW 2358, Australia.
F CSIRO Ecosystem Sciences, 37 Graham Road, Highett, Vic. 3190, Australia.
G Corresponding author. Email: Andrew.Higgins@csiro.au
The Rangeland Journal 35(2) 181-191 https://doi.org/10.1071/RJ12090
Submitted: 2 November 2012 Accepted: 2 May 2013 Published: 27 May 2013
Abstract
Despite the longevity, scale and importance of northern Australia’s beef industry, recent disruptions to external markets have demonstrated a degree of vulnerability to shocks in the supply chain. Matching the industry’s long-evident resilience to climatic variability with resilience to changes in markets and supply chains requires careful planning. One component of this is how investments in infrastructure will need to be planned to facilitate adaptive responses to market changes. This paper provides an outline of a modelling framework that links strategic and operational dynamic models of logistics along the supply chain from the property to the abattoir or port. A novelty of the methodology is that it takes into account the high granularity of individual livestock transport vehicle movements and the ability to scale up to an almost complete view of logistics costs across the entire beef industry of northern Australia. The paper illustrates how the methodology could be used to examine the effects of changes in logistics infrastructure on efficiency and costs using examples from the states of Northern Territory, Western Australia and Queensland.
Additional keywords: beef, infrastructure, northern Australia, simulation, transport.
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