An optimisation-based seasonal sugarcane harvest scheduling decision support system for commercial growers in South Africa

An ongoing sugarcane decision support research project in South Africa is aimed at developing a decision support system capable of providing computerised support to those charged with the task of scheduling sugarcane harvesting operations in South Africa. In situations where the number of fields is...

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Bibliographic Details
Published in:Computers and electronics in agriculture 2012-04, Vol.83, p.21-31
Main Authors: Stray, B.J, van Vuuren, J.H, Bezuidenhout, C.N
Format: Article
Language:English
Subjects:
Agronomy. Soil science and plant productions
Biological and medical sciences
crops
decision support systems
Fundamental and applied biological sciences. Psychology
growers
harvesting
Metaheuristic
Regression analysis
research support
Sugarcane
Travelling salesman problem
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Summary:An ongoing sugarcane decision support research project in South Africa is aimed at developing a decision support system capable of providing computerised support to those charged with the task of scheduling sugarcane harvesting operations in South Africa. In situations where the number of fields is large and when the conditions under which the crops are growing change frequently—for example as a result of climatic, biological or management-related events—computerised support is applicable. Commercial growers have provided data suitable for regression modelling of the parameters that govern the values and costs involved, and have participated in two consecutive preliminary system evaluation and development experiments conducted during the 2009 and 2010 harvesting seasons. The optimisation models underlying the decision support system are based on a time-dependent travelling salesman problem formulation and are solved approximately by means of a tabu search in a Microsoft Visual Basic for Applications (VBA) for Excel environment. The growers who participated in the evaluation experiments responded positively to the decision support system and stated that it may be useful to large-scale sugarcane producers as well as emerging growers. The authors’ findings are that the decision support system provides support in practical sugarcane harvest scheduling and that one series of regression fits is required for each agroclimatically and management-wise homogenous area.
ISSN:0168-1699
1872-7107
DOI:10.1016/j.compag.2012.01.009