Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/701
Title: A two-stage stochastic programming with recourse model for determining robust planting plans in horticulture
Authors: Darby-Dowman, K
Barker, S
Audsley, E
Parsons, D
Keywords: Linear programming;Stochastic programming;Agriculture;Planning
Issue Date: 2000
Publisher: Palgrave Macmillan
Citation: This is a post-peer-review, pre-copyedit version of an article published in The Journal of the Operational Research Society. The definitive publisher-authenticated version Journal of the Operational Research Society, Volume 51, Number 1, 1 January 2000, pp. 83-89(7) is available online at:http://www.palgrave-journals.com/jors/journal/v51/n1/abs/2600858a.html
Series/Report no.: The Centre for the Analysis of Risk and Optimisation Modelling Applications (CARISMA), Brunel University;Technical Reports
Abstract: A two-stage stochastic programming with recourse model for the problem of determining optimal planting plans for a vegetable crop is presented in this paper. Uncertainty caused by factors such as weather on yields is a major influence on many systems arising in horticulture. Traditional linear programming models are generally unsatisfactory in dealing with the uncertainty and produce solutions that are considered to involve an unacceptable level of risk. The first stage of the model relates to finding a planting plan which is common to all scenarios and the second stage is concerned with deriving a harvesting schedule for each scenario. Solutions are obtained for a range of risk aversion factors that not only result in greater expected profit compared to the corresponding deterministic model, but also are more robust.
URI: http://bura.brunel.ac.uk/handle/2438/701
Appears in Collections:Dept of Mathematics Research Papers
Mathematical Sciences

Files in This Item:
File Description SizeFormat 
akhd-2.pdf55.31 kBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.