Finding the 'faster' path in vehicle routing

• Main Authors: GUO, Jing, WU, Yaoxin, ZHANG, Xuexi, ZHANG, Le, CHEN, Wei, CAO, Zhiguang, GUO, Hongliang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Vehicle routing; Normal distribution; Bidelta distribution; Road link; Theoretical models; Arbitrary path; Link travel time; Artificial network; Binormal distribution modelling; Real road network; Real traffic data; Probability density function; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/8206; https://ink.library.smu.edu.sg/context/sis_research/article/9209/viewcontent/Finding_the__faster__path_in_vehicle_routing.pdf
• Institution: Singapore Management University

In this study, the authors improve the faster criterion in vehicle routing by extending the bi-delta distribution to the bi-normal distribution, which is a reasonable assumption for travel time on each road link. Based on this assumption, theoretical models are built for an arbitrary path and subsequently adopted to evaluate two candidate paths through probabilistic comparison. Experimental results demonstrate the bi-normal behaviour of link travel time in practice, and verify the faster criterion's superiority in determining the optimal path either on an artificial network with bi-normal distribution modelling link travel time or on a real road network with real traffic data. This study also validates that when the link number of one path is large, the probability density function of the whole path can be simplified by a normal distribution which approximates the sum of bi-normal distributions for each link.