Michael Young, John Young, Ross S. Kingwell, Philip E. Vercoe
{"title":"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","authors":"Michael Young, John Young, Ross S. Kingwell, Philip E. Vercoe","doi":"10.1111/1467-8489.12539","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1467-8489.12539","citationCount":"0","resultStr":"{\"title\":\"Representing weather-year variation in whole-farm optimisation models: Four-stage single-sequence vs eight-stage multi-sequence\",\"authors\":\"Michael Young, John Young, Ross S. Kingwell, Philip E. Vercoe\",\"doi\":\"10.1111/1467-8489.12539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1467-8489.12539\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1467-8489.12539\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1467-8489.12539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Representing weather-year variation in whole-farm optimisation models: Four-stage single-sequence vs eight-stage multi-sequence
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.