Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

被引:41
作者
deVoil, P.
Rossing, W. A. H.
Hammer, G. L.
机构
[1] Queensland Dept Primary Ind & Fisheries, Agr Prod Syst Res Unit, Toowoomba, Qld 4350, Australia
[2] Univ Wageningen & Res Ctr, Biol Farming Syst Grp, NL-6709 PG Wageningen, Netherlands
[3] Univ Queensland, Sch Land & Food Sci, Brisbane, Qld 4072, Australia
关键词
evolutionary algorithms; agricultural systems modelling; cropping system design; profit; sustainability; APSIM;
D O I
10.1016/j.envsoft.2005.04.016
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier "peels" or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives. Crown Copyright (c) 2005 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1368 / 1374
页数:7
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