{"title":"Optimizing Harvest Planning in Perishable Agricultural Production: A Data-Driven Approach Leveraging Weather Conditions and Clustering Analysis","authors":"Mesut Samasti, Tarik Kucukdeniz","doi":"10.1002/fes3.70107","DOIUrl":null,"url":null,"abstract":"<p>In the rapidly evolving and competitive sector of agricultural production, optimizing operational efficiencies is crucial for the sustainability of enterprises. This study introduces a novel approach to enhance the profitability and sustainability of perishable food production enterprises by optimizing harvest planning and logistics activities, which are significantly influenced by weather conditions. Using the weighted fuzzy c-means (WFCM) method, a two-stage solution approach was developed to improve the decision-making process in both short- and long-term operational planning. In the first stage, clustering analysis was conducted to determine optimal facility locations and assign fields to these facilities, thereby facilitating the efficient processing of perishable food products. Following this, an integer linear programming model was developed to optimize the harvest plan, considering the variable weather-related costs and maximizing the total operating profit. This innovative approach not only considers the economic value of the product, which fluctuates over time, but also integrates weather precipitation data to dynamically adjust the harvesting plan, thereby minimizing costs and maximizing revenues. The model was rigorously tested using real data from 16 sugar factories in Türkiye and their corresponding sugar beet fields. The results demonstrated a substantial potential increase in operating profit by 27.47% compared with the current scenario. Furthermore, the model promises to reduce economic losses associated with improper storage and stacking and to stabilize seasonal fluctuations in vehicle supply and freight prices by distributing vehicle demand over a longer period. This study adds a significant layer to the existing literature, offering a comprehensive solution that addresses the complex interplay of various factors in agricultural production and setting the stage for more resilient and sustainable operations in the perishable food sector.</p>","PeriodicalId":54283,"journal":{"name":"Food and Energy Security","volume":"14 3","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fes3.70107","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food and Energy Security","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/fes3.70107","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In the rapidly evolving and competitive sector of agricultural production, optimizing operational efficiencies is crucial for the sustainability of enterprises. This study introduces a novel approach to enhance the profitability and sustainability of perishable food production enterprises by optimizing harvest planning and logistics activities, which are significantly influenced by weather conditions. Using the weighted fuzzy c-means (WFCM) method, a two-stage solution approach was developed to improve the decision-making process in both short- and long-term operational planning. In the first stage, clustering analysis was conducted to determine optimal facility locations and assign fields to these facilities, thereby facilitating the efficient processing of perishable food products. Following this, an integer linear programming model was developed to optimize the harvest plan, considering the variable weather-related costs and maximizing the total operating profit. This innovative approach not only considers the economic value of the product, which fluctuates over time, but also integrates weather precipitation data to dynamically adjust the harvesting plan, thereby minimizing costs and maximizing revenues. The model was rigorously tested using real data from 16 sugar factories in Türkiye and their corresponding sugar beet fields. The results demonstrated a substantial potential increase in operating profit by 27.47% compared with the current scenario. Furthermore, the model promises to reduce economic losses associated with improper storage and stacking and to stabilize seasonal fluctuations in vehicle supply and freight prices by distributing vehicle demand over a longer period. This study adds a significant layer to the existing literature, offering a comprehensive solution that addresses the complex interplay of various factors in agricultural production and setting the stage for more resilient and sustainable operations in the perishable food sector.
期刊介绍:
Food and Energy Security seeks to publish high quality and high impact original research on agricultural crop and forest productivity to improve food and energy security. It actively seeks submissions from emerging countries with expanding agricultural research communities. Papers from China, other parts of Asia, India and South America are particularly welcome. The Editorial Board, headed by Editor-in-Chief Professor Martin Parry, is determined to make FES the leading publication in its sector and will be aiming for a top-ranking impact factor.
Primary research articles should report hypothesis driven investigations that provide new insights into mechanisms and processes that determine productivity and properties for exploitation. Review articles are welcome but they must be critical in approach and provide particularly novel and far reaching insights.
Food and Energy Security offers authors a forum for the discussion of the most important advances in this field and promotes an integrative approach of scientific disciplines. Papers must contribute substantially to the advancement of knowledge.
Examples of areas covered in Food and Energy Security include:
• Agronomy
• Biotechnological Approaches
• Breeding & Genetics
• Climate Change
• Quality and Composition
• Food Crops and Bioenergy Feedstocks
• Developmental, Physiology and Biochemistry
• Functional Genomics
• Molecular Biology
• Pest and Disease Management
• Post Harvest Biology
• Soil Science
• Systems Biology