一种用于路线距离最小化的智能技术,使用计算优化算法来存储和销售作物
Saikat Banerjee1, Abhoy Chand Mondal2
1The department of Computer Applications, Vivekananda Mahavidyalaya, Haripal, Hooghly, West Bengal, India. saikat.banerjee56@gmail.com.
Scientific reports
|August 6, 2025
概括
使用计算智能算法优化印度的冷库路线可以显著降低农民的成本. 殖民地算法在寻找农业物流最有效的路径方面被证明是最有效的.
科学领域:
- 运营研究 运营研究
- 计算机科学 计算机科学
- 农业物流 农业物流
背景情况:
- 印度的农业部门面临储存缺口,尽管产量增长.
- 优化冷库路线对于农民的利能力至关重要.
- 旅行销售员问题 (TSP) 是一个关键的优化挑战.
研究的目的:
- 在印度的多个冷藏设施之间开发高效的连接.
- 应用计算智能算法来解决农业冷链的TSP.
- 确定最有效的算法,以尽量减少冷藏库路线距离.
主要方法:
- 该研究使用了几种计算智能算法:贪算法,模拟化,2-opt算法,粒子群集优化和群优化.
- 这些算法被用来解决旅行销售员问题,以优化冷藏设施的路线.
- 路线效率的评估是基于尽量减少旅行距离和时间.
主要成果:
- 殖民地优化算法在找到最有效的路线方面表现出卓越的性能.
- 所有测试的计算智能算法都为TSP提供了用于冷库连接的解决方案.
- 这项研究证实了计算智能在优化农业物流中的应用性.
结论:
- 殖民地优化是优化印度冷库路线的高效方法.
- 实施优化路线可以提高印度农业冷藏行业的成本效益和效率.
- 计算智能为解决农业中复杂的物流挑战提供了强大的工具.
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