Open AccessVehicle routing problem solution considering minimising fuel consumption
Author(s) -
Yao Enjian,
Lang Zhifeng,
Yang Yang,
Zhang Yongsheng
Publication year - 2015
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2015.0027
Subject(s) - fuel efficiency , energy consumption , vehicle routing problem , computer science , routing (electronic design automation) , beijing , mathematical optimization , consumption (sociology) , environmental pollution , operations research , automotive engineering , engineering , computer network , environmental science , mathematics , social science , environmental protection , electrical engineering , china , sociology , law , political science
Recently, logistics is not only playing more and more important role in social and economic development, but also caused serious energy consumption and environment pollution problems. Reasonable vehicle route planning is viewed as an important solution to reduce logistics enterprises’ operation costs as well as alleviate the energy and environmental problems. This study aims to propose a solution to time‐dependent vehicle routing problem with time windows (TDVRPTW) considering minimising fuel consumption. First, a mathematical TDVRPTW model with the minimum fuel consumption as an objective function is established, in which the three‐dimensional bin‐packing problem is considered as a sub‐problem and the alternative stop point concept is newly proposed to reduce the possible detouring distance and fuel consumption of logistic vehicle. Then, an ant colony algorithm is applied to solve the problem, and the departure time optimisation is introduced to further improve the obtained results. Finally, the proposed approach is evaluated with the real road network and traffic data of Beijing. The results show that the method introduced in this study outperforms the existing approaches in reducing fuel consumption as well as route length.