优化和公共交通招标:意大利南部的一个案例研究
Vincenzo Corvello1, Roberto Musmanno2, Giuseppe Pavone3
1Dipartimento di Ingegneria, Università di Messina, 98166 Messina, Italy.
概括
本研究引入了一种新的启发式算法,用于优化意大利的公共交通批量. 该方法平衡成本和服务水平,为运输网络设计提供高质量的解决方案.
科学领域:
- 运营研究 运营研究
- 运输科学 运输科学
- 启发式算法 启发式算法
背景情况:
- 公共交通组织在设计最佳路线时面临着挑战.
- 平衡成本和服务水平对于高效的公共交通运营至关重要.
- 现有的模型可能无法完全解决现实世界地块设计的复杂性.
研究的目的:
- 开发和介绍一个多启动启发式方法,以实现公共交通中最佳的批量设计.
- 以图形分区问题为模型,将批量设计问题作为图形分区问题.
- 将成本和服务水平的考虑纳入优化过程中.
主要方法:
- 使用一个多启动启发式算法.
- 适应性大邻里搜索 (ALNS) 用于解决方案优化.
- 这个问题被建模为图形分区问题.
主要成果:
- 拟议的算法为公共交通批量设计问题确定了高质量的解决方案.
- 基于意大利南部真实数据的计算研究结果.
- 该方法有效地平衡了成本和服务水平目标.
结论:
- 多启动启发式算法为优化公共交通批量设计提供了一种有效的方法.
- 该方法适用于意大利运输系统中的现实场景.
- 这项研究有助于提高公共交通组织的效率和服务质量.
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