Improved simulated annealing algorithm for time-dependent electric vehicle routing problem

Electric vehicle distribution has short mileage, strong time dependence, and is more vulnerable to road congestion in urban road networks. In order to solve the problem of high distribution cost of electric vehicles in urban road network, a time-dependent electric vehicle distribution path optimization model is constructed. Firstly, a vehicle power consumption measurement model considering vehicle parameters, environmental factors and road impedance is established. On this basis, a mathematical model is constructed to minimize the sum of fixed cost, use cost, power consumption cost and time window penalty cost. Secondly, an improved simulated annealing algorithm is designed to enhance its global search ability and the ability to jump out of local optimum. Thirdly, according to the actual example of a comprehensive supermarket in X city, the effectiveness of the proposed algorithm is verified. The experimental results show that compared with the traditional simulated annealing algorithm, the proposed algorithm has better solution efficiency and solution performance, which brings some enlightenment to logistics distribution enterprises.