Abstract
To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas’ theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method. During genetic manipulation, different interlacing and mutation operations are carried out on different chromosomes, while, during population evolution, the infeasible solution is naturally avoided. A part of the road network of Xifeng District in Qingyang City is taken as an example to test the model and the algorithm in this study, and the concrete transportation paths are utilized in the final distribution scheme. Therefore, more robust EV distribution paths with multiple distribution centers can be obtained using the robust optimization model.
Highlights
The rapid development of e-commerce has a significant impact on our daily lives and has driven the improvement of the logistics industry in cities
He et al were in order to solve the problem of battery electric vehicles (BEVs) drivers select routes, formulated three mathematical models to describe the resulting network equilibrium flow distributions and found the optimal path [14]
The interval value used in this study represents the uncertainty road link time of the electrical vehicle (EV) distribution path problem with multiple distribution centers, that is, ~tij, ~tij 2 1⁄2tij; tij þ dij, where the nominal value of road link ij is generated from the ratio of road distance sij and EV running velocity v
Summary
The rapid development of e-commerce has a significant impact on our daily lives and has driven the improvement of the logistics industry in cities. The optimization and scheduling model of the electric logistics vehicle are established to avoid long distribution time and useless route, and suitable recharging stations were chosen when the remaining mileage was not enough to meet the distribution demands [9]. Liu et al aimed at the problem about EV navigation system multiple charging in a long O-D trip, provided Improved Chrono-SPT (ISC) to derive the optimal decision sequence, to achieve the purpose of finding out an optimal routing and charging policy [13] He et al were in order to solve the problem of battery electric vehicles (BEVs) drivers select routes, formulated three mathematical models to describe the resulting network equilibrium flow distributions and found the optimal path [14]. EV of distribution center p0 services for client nodes i; i 2 P1; p0 2 P0; k 2 Vp0 otherwise
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