Roberto Da Silva Gervasio Pontes , Diego Nunes Brandão , Fábio Luiz Usberti , Laura Silva De Assis
{"title":"轮作规划问题的多目标模型","authors":"Roberto Da Silva Gervasio Pontes , Diego Nunes Brandão , Fábio Luiz Usberti , Laura Silva De Assis","doi":"10.1016/j.agsy.2024.104050","DOIUrl":null,"url":null,"abstract":"<div><h3>CONTEXT</h3><p>Agriculture is a vital component of the global economy and modern societies. It has undergone significant consolidation and transformation in response to the food supply crisis, highlighting the important relationship between humans and the environment. However, concerns remain about food security, particularly with the projected population growth of over 9.5 billion by 2050. The computerization of agri-food supply chains has emerged as a significant response to these challenges.</p></div><div><h3>OBJECTIVE</h3><p><em>(1)</em> Develop a multi-objective model that explores both net return and crop diversity. <em>(2)</em> Solve the problem using techniques that guarantee optimality. <em>(3)</em> Evaluate the gain in crop diversity versus the net return of the optimized configuration.</p></div><div><h3>METHODS</h3><p>The study presents four Multi-objective Mixed-Integer Linear Programming models with integer and binary decision variables for Crop Rotation Planning Problems. The objectives are to maximize net income and increase crop diversity and land utilization.</p></div><div><h3>RESULTS AND CONCLUSIONS</h3><p>The study exclusively employs linear programming techniques to solve the models resulting in an optimal solution. A comparative analysis with existing models in the literature, which primarily focused on maximizing net income, yielded a noteworthy result. The proposed models demonstrate an average increase of 60% in crop diversity, with net return losses of less than 5%.</p></div><div><h3>SIGNIFICANCE</h3><p>In conclusion, this research provides valuable information for crop rotation planning and highlights the importance of agricultural farm management and precision agriculture in addressing current challenges. The innovative nature of this research is exemplified by the use of mixed-integer linear programming techniques to solve a multi-objective problem with integer and binary variables. The obtained results demonstrate increased crop diversity and minimal economic losses, which have significant implications for several areas of agricultural science, policy, and practice.</p></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"219 ","pages":"Article 104050"},"PeriodicalIF":6.1000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective models for crop rotation planning problems\",\"authors\":\"Roberto Da Silva Gervasio Pontes , Diego Nunes Brandão , Fábio Luiz Usberti , Laura Silva De Assis\",\"doi\":\"10.1016/j.agsy.2024.104050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>CONTEXT</h3><p>Agriculture is a vital component of the global economy and modern societies. It has undergone significant consolidation and transformation in response to the food supply crisis, highlighting the important relationship between humans and the environment. However, concerns remain about food security, particularly with the projected population growth of over 9.5 billion by 2050. The computerization of agri-food supply chains has emerged as a significant response to these challenges.</p></div><div><h3>OBJECTIVE</h3><p><em>(1)</em> Develop a multi-objective model that explores both net return and crop diversity. <em>(2)</em> Solve the problem using techniques that guarantee optimality. <em>(3)</em> Evaluate the gain in crop diversity versus the net return of the optimized configuration.</p></div><div><h3>METHODS</h3><p>The study presents four Multi-objective Mixed-Integer Linear Programming models with integer and binary decision variables for Crop Rotation Planning Problems. The objectives are to maximize net income and increase crop diversity and land utilization.</p></div><div><h3>RESULTS AND CONCLUSIONS</h3><p>The study exclusively employs linear programming techniques to solve the models resulting in an optimal solution. A comparative analysis with existing models in the literature, which primarily focused on maximizing net income, yielded a noteworthy result. The proposed models demonstrate an average increase of 60% in crop diversity, with net return losses of less than 5%.</p></div><div><h3>SIGNIFICANCE</h3><p>In conclusion, this research provides valuable information for crop rotation planning and highlights the importance of agricultural farm management and precision agriculture in addressing current challenges. The innovative nature of this research is exemplified by the use of mixed-integer linear programming techniques to solve a multi-objective problem with integer and binary variables. The obtained results demonstrate increased crop diversity and minimal economic losses, which have significant implications for several areas of agricultural science, policy, and practice.</p></div>\",\"PeriodicalId\":7730,\"journal\":{\"name\":\"Agricultural Systems\",\"volume\":\"219 \",\"pages\":\"Article 104050\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural Systems\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0308521X24002002\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Systems","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0308521X24002002","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Multi-objective models for crop rotation planning problems
CONTEXT
Agriculture is a vital component of the global economy and modern societies. It has undergone significant consolidation and transformation in response to the food supply crisis, highlighting the important relationship between humans and the environment. However, concerns remain about food security, particularly with the projected population growth of over 9.5 billion by 2050. The computerization of agri-food supply chains has emerged as a significant response to these challenges.
OBJECTIVE
(1) Develop a multi-objective model that explores both net return and crop diversity. (2) Solve the problem using techniques that guarantee optimality. (3) Evaluate the gain in crop diversity versus the net return of the optimized configuration.
METHODS
The study presents four Multi-objective Mixed-Integer Linear Programming models with integer and binary decision variables for Crop Rotation Planning Problems. The objectives are to maximize net income and increase crop diversity and land utilization.
RESULTS AND CONCLUSIONS
The study exclusively employs linear programming techniques to solve the models resulting in an optimal solution. A comparative analysis with existing models in the literature, which primarily focused on maximizing net income, yielded a noteworthy result. The proposed models demonstrate an average increase of 60% in crop diversity, with net return losses of less than 5%.
SIGNIFICANCE
In conclusion, this research provides valuable information for crop rotation planning and highlights the importance of agricultural farm management and precision agriculture in addressing current challenges. The innovative nature of this research is exemplified by the use of mixed-integer linear programming techniques to solve a multi-objective problem with integer and binary variables. The obtained results demonstrate increased crop diversity and minimal economic losses, which have significant implications for several areas of agricultural science, policy, and practice.
期刊介绍：
Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments.
The scope includes the development and application of systems analysis methodologies in the following areas:
Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making;
The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment;
Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems;
Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.
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