Research by Zhitao Xu that proposes a new model for capacitated green vehicle routing problem in Computers & Industrial Engineering on Oct. 2019. CIE concerns the original contributions on the new computerized applications to problems of interest in the broad industrial engineering and associated communities. CIE is on the Q1 level in JCR ranking scheme in both of the industrial engineering and the computer sciences communities. It is also rated as 3 star according to ABS ranking list. 

Our paper investigates the capacitated green vehicle routing problem with time-varying vehicle speed and soft time windows. The main contribution of this paper is to provide a new approach to modeling the non-linear time-varying vehicle speed and evaluating trade-offs between customer satisfaction and the fuel consumption in GVRP with urban traffic congestion consideration. An improved NSGA-II with adaptive strategies and greedy strategies is developed to solve the GVRP. We observe that the increase in speed divisions (as is common in existing literature) in models has a very limited effect on the fuel consumption and customer satisfaction in GVRP, but it results in to a large amount of computation. It is of great significance for urban carriers in a big data environment, where the real-time data of the road speeds can be obtained and it can be fitted and represented by a continuous function. This study offers a practical method for green vehicle routing in a big data environment.

Fig.1 Traveling speeds during the planning horizon 

If you are interested in the research, please read the paper

Zhitao Xu, Adel Elomri, Shaligram Pokharel, Fatih Mutlu, A model for capacitated green vehicle routing problem with the time-varying vehicle speed and soft time windows [J], Computers & Industrial Engineering,. 2019, https://doi.org/10.1016/j.cie.2019.106011.

A full version of this article is available at: 

https://www.sciencedirect.com/science/article/pii/S0360835219304693