Multi-objective models for crop rotation planning problems

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Agricultural Systems Pub Date : 2024-07-11 DOI:10.1016/j.agsy.2024.104050

Roberto Da Silva Gervasio Pontes , Diego Nunes Brandão , Fábio Luiz Usberti , Laura Silva De Assis

{"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}

引用次数: 0

Abstract

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.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

轮作规划问题的多目标模型

内容提要农业是全球经济和现代社会的重要组成部分。为应对粮食供应危机，农业经历了重大的整合和转型，凸显了人类与环境之间的重要关系。然而，粮食安全问题依然令人担忧，特别是预计到 2050 年人口将增长到 95 亿以上。农业食品供应链的计算机化已成为应对这些挑战的重要措施。目标(1) 建立一个多目标模型，探索净收益和作物多样性。(2) 使用保证最优的技术解决问题。(3) 评估作物多样性的收益与优化配置的净收益。结果与结论本研究专门采用线性规划技术来求解模型，从而得出最优解。与文献中主要关注净收入最大化的现有模型进行比较分析，得出了值得注意的结果。总之，这项研究为轮作规划提供了有价值的信息，并强调了农业农场管理和精准农业在应对当前挑战方面的重要性。这项研究的创新性体现在使用混合整数线性规划技术来解决一个包含整数和二进制变量的多目标问题。研究结果表明，作物多样性得到了提高，经济损失降到了最低，这对农业科学、政策和实践的多个领域具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Agricultural Systems 农林科学-农业综合

CiteScore

13.30

自引率

7.60%

发文量

174

审稿时长

30 days

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.