An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms
Abstract India’s agriculture sector has shown sustained growth in production levels over time. However, the current production level regarding food storage has not been adequately matched, emphasizing the existing gap in the Indian agricultural cold storage industry. Optimizing the route for cold st...
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Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-14263-x |
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| author | Saikat Banerjee Abhoy Chand Mondal |
| author_facet | Saikat Banerjee Abhoy Chand Mondal |
| author_sort | Saikat Banerjee |
| collection | DOAJ |
| description | Abstract India’s agriculture sector has shown sustained growth in production levels over time. However, the current production level regarding food storage has not been adequately matched, emphasizing the existing gap in the Indian agricultural cold storage industry. Optimizing the route for cold storage is cost-effective for farmers. The traveling salesperson problem is a well-known algorithmic issue in computer science and operations research, explicitly emphasizing optimization. The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. Computational intelligence algorithms focus on computer techniques that enable machines to improve their performance by analyzing data without explicit programming. Computational intelligence algorithms are employed to address conventional mathematical problems. This research aims to develop connectivity across many cold storage facilities utilizing the traveling salesperson problem algorithm. Various computational intelligence algorithms such as Greedy Algorithm, Simulated Annealing, 2-opt Algorithm, Particle Swarm Optimization, and Ant Colony Optimization are employed to determine the minimum route. The experimental findings demonstrate that the ant colony algorithm yields superior outcomes. |
| format | Article |
| id | doaj-art-dda4ca944111492db8b9d53901126650 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-dda4ca944111492db8b9d539011266502025-08-20T03:45:48ZengNature PortfolioScientific Reports2045-23222025-08-0115112210.1038/s41598-025-14263-xAn intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithmsSaikat Banerjee0Abhoy Chand Mondal1The department of Computer ApplicationsThe department of Computer Science, The University of BurdwanAbstract India’s agriculture sector has shown sustained growth in production levels over time. However, the current production level regarding food storage has not been adequately matched, emphasizing the existing gap in the Indian agricultural cold storage industry. Optimizing the route for cold storage is cost-effective for farmers. The traveling salesperson problem is a well-known algorithmic issue in computer science and operations research, explicitly emphasizing optimization. The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. Computational intelligence algorithms focus on computer techniques that enable machines to improve their performance by analyzing data without explicit programming. Computational intelligence algorithms are employed to address conventional mathematical problems. This research aims to develop connectivity across many cold storage facilities utilizing the traveling salesperson problem algorithm. Various computational intelligence algorithms such as Greedy Algorithm, Simulated Annealing, 2-opt Algorithm, Particle Swarm Optimization, and Ant Colony Optimization are employed to determine the minimum route. The experimental findings demonstrate that the ant colony algorithm yields superior outcomes.https://doi.org/10.1038/s41598-025-14263-xCropCold storageRouteTraveling salesman problem (TSP)Greedy algorithmAnt colony optimization (ACO) |
| spellingShingle | Saikat Banerjee Abhoy Chand Mondal An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms Scientific Reports Crop Cold storage Route Traveling salesman problem (TSP) Greedy algorithm Ant colony optimization (ACO) |
| title | An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| title_full | An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| title_fullStr | An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| title_full_unstemmed | An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| title_short | An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| title_sort | intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms |
| topic | Crop Cold storage Route Traveling salesman problem (TSP) Greedy algorithm Ant colony optimization (ACO) |
| url | https://doi.org/10.1038/s41598-025-14263-x |
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