Route Optimization of Electric Vehicle considering Soft Time Windows and Two Ways of Power Replenishment

Abstract

Under the background of severe air pollution and energy shortage, electric vehicles (EVs) are promising vehicles to support green supply chain and clean production. In the world, the renewal of EVs has become a general trend. Therefore, the concern about EVs is a hot issue at present, but EVs have the characteristics of limited driving distance and long charging time. When the EVs are used in logistics transportation, these characteristics have a significant impact on the vehicle routing problems. Therefore, based on the research experience of traditional vehicle routing optimization, combining with the characteristics of EVs, this paper presents an optimal problem of electric vehicle routes with time windows based on two charging methods and it also designs a mathematical model which was caused by early and late arrival as the objective function to minimize the transportation cost, vehicle use cost, power supply cost, and penalty cost. The model is solved using an ant colony algorithm. Finally, the ant colony algorithm is tested and analysed with an example.

A heterogeneous electric taxi fleet routing problem with recharging stations to maximize the company’s profit

“…Normally charged, and finally, for both conductive charging and battery replacement options where conventional charging stations are used to replace batteries while customers location are used for conductive charging. Meng and Ma [21] presented an optimization problem for routing electric vehicles with time windows based on two charging methods and solved their model using the ant colony algorithm. Sayarshad et al [31] studied the problem of dynamic routing of electric taxis with battery replacement stations with a predictive policy using the Markov decision-making process to allocate the fleet of electric taxis to customers on the assumption of elastic demand.…”

“…Constraints (19) and ( 20) cover arrival and end times at any time after customers leave and cover it after leaving the charging station, depending on the time to charge the battery. Arrival times within time windows are guaranteed by constraints (21) for both customers and charging station nodes. Constraints ( 22) and ( 23) define the acceptable values for 𝑥 𝑘 𝑖𝑗 and 𝑤 𝑘 𝑖𝑗 .…”

Green Vehicle Routing Problem: State of the Art and Future Directions

“…While EV battery packs are capable of supporting travel in the 100mile range on a single charge, in order to replenish their batteries, they need to have access to charging stations. Meng and Ma [42] explored electric vehicle routing with soft time windows and offered two ways of power replenishment. The design of mobile charging stations have been investigated by Huang et al [43].…”

A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification

“…Xiao et al [71] introduced the energy/electricity consumption rate (ECR) per unit of traveled distance into the E-VRP-TW for the first time. Meng and Ma [72] presented a new problem by calculating more accurate cost of the logistics includes fixed, transportation, charging, and time-windows violation penalty costs and combining the two charging strategies of fast charging and battery swapping and each EV can charge its battery or replace it according to the minimum of the battery replacement time and fast charging time. In order to optimize resource allocation, and reduce energy consumption and road congestion, soft time-windows was considered in this study.…”