  Logistics has gained great attentions with the prosperous development of
commerce, which is often seen as the classic optimal vehicle routing problem.
Meanwhile, electric vehicle (EV) has been widely used in logistic fleet to curb
the emission of green house gases in recent years. Solving the optimization
problem of joint routing and charging of multiple EVs is in a urgent need,
whose objective function includes charging time, charging cost, EVs travel
time, usage fees of EV and revenue from serving customers. This joint problem
is formulated as a mixed integer programming (MIP) problem, which, however, is
NP-hard due to integer restrictions and bilinear terms from the coupling
between routing and charging decisions. The main contribution of this paper
lies at proposing an efficient two stage algorithm that can decompose the
original MIP problem into two linear programming (LP) problems, by exploiting
the exactness of LP relaxation and eliminating the coupled term. This algorithm
can achieve a nearoptimal solution in polynomial time. In addition, another
variant algorithm is proposed based on the two stage one, to further improve
the quality of solution.
