Multi Depot Vehicle Routing Using Ant Colony Optimization - Trip Assignment of Freight Flow Using Modified Gravity Model: Special case of CPEC – Flagship of Belt and Road Initiative (BRI)

Husnain Saeed, Shahid Ikramullah, Mushtaq Khan, Fahd Amjad, Liaqat Ali, Z. Faping
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Abstract

Various optimization techniques have been used to solve Traffic Assignment problem, similarly different variants of Gravity Model have been used to generate the trips across the network. This paper presents a unique methodology of combining both techniques and presents a holistic framework of managing Transportation Corridors that emerged due to combining these two proven techniques with slight modifications. Modified Gravity Model (MGM) successfully predicted and generated the trips across a corridor, and Ant Colony Optimization (ACO) helped assign Trips. The data used has been obtained from a real-life Corridor and the results have been verified using statistics from the national authorities managing the corridor. Specific case of China Pakistan Economic Corridor (CPEC) has been considered and modeled in Simio, Matlab and QGIS.
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基于蚁群优化的多车场车辆路径选择——基于修正重力模型的货流行程分配——以中巴经济走廊为例——“一带一路”旗舰项目
各种优化技术已被用于解决交通分配问题,类似地,重力模型的不同变体已被用于生成跨网络的行程。本文提出了一种结合这两种技术的独特方法,并提出了一个管理运输走廊的整体框架,该框架是由于将这两种经过验证的技术稍加修改而结合起来而出现的。修正的重力模型(MGM)成功地预测和生成了穿越走廊的行程,蚁群优化(ACO)帮助分配了行程。所使用的数据来自现实生活中的走廊,并使用管理走廊的国家当局的统计数据对结果进行了核实。考虑了中巴经济走廊(CPEC)的具体案例,并在Simio、Matlab和QGIS中进行了建模。
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