Representing weather-year variation in whole-farm optimisation models: Four-stage single-sequence vs eight-stage multi-sequence

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-11-05 DOI:10.1111/1467-8489.12539
Michael Young, John Young, Ross S. Kingwell, Philip E. Vercoe
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Abstract

The trade-off between accuracy and complexity is a common issue faced in farm systems analysis. To provide insights into the importance of representing weather-year sequence in farm modelling, two whole-farm optimisation models are constructed and applied to a mixed enterprise farming system in a subregion of Western Australia. The frameworks are (i) four-stage single-sequence stochastic programming with recourse (4-SPR) to capture weather-year variation and management tactics tailored to each weather-year and (ii) eight-stage multi-sequence stochastic programming with recourse (8-SPR) to outline weather-year sequences and management tactics tailored to particular weather-year sequences. Results show that single-year stochastic programming generates similar expected profit and strategic management as multi-year stochastic programming. However, optimal tactical farm management is affected by the outcome of the previous year. Tactical decision-making in response to the outcome of the preceding weather-year increases profitability by 14%. Technology changes over the last decade, particularly the increase in computer speed and computational power, increase the ease of construction and application of the 4-SPR and 8-SPR frameworks. Nonetheless, choosing which framework is best to apply to a particular issue or opportunity remains a challenge.

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在全农场优化模型中体现天气年变化:四阶段单序列与八阶段多序列比较
准确性与复杂性之间的权衡是农场系统分析中面临的共同问题。为了深入了解在农场建模中体现天气年序列的重要性,我们构建了两个全农场优化模型,并将其应用于西澳大利亚一个次区域的混合企业农业系统。这两个框架分别是:(i) 带追索权的四阶段单序列随机程序设计(4-SPR),用于捕捉天气年变化和针对每个天气年的管理策略;(ii) 带追索权的八阶段多序列随机程序设计(8-SPR),用于概述天气年序列和针对特定天气年序列的管理策略。结果表明,单年随机规划产生的预期利润和战略管理与多年随机规划相似。然而,农场的最佳战术管理受到前一年结果的影响。根据上一天气年的结果做出的战术决策使利润率提高了 14%。过去十年的技术变革,特别是计算机速度和计算能力的提高,使 4-SPR 和 8-SPR 框架的构建和应用更加容易。然而,选择哪种框架最适合应用于特定问题或机遇仍然是一项挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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