Abstract: With the substantial support from government and development of environmental awareness, electric vehicles grow more and more popular in logistics fields. Small package shipping is in the back end of logistics distribution and performs deliveries from local deports to customers. Logistic operational cost may be affected by many factors, including heterogeneous vehicles, staff assignment and differentiated service time. An effective utilization of logistics deliverer can bring economic benefits, which has been paid more attention by logistics enterprise gradually. Logistics distribution service needs the cooperation of the professional delivery staffs, electric vehicles and numerous customers, with a great deal of interplay between staff assignment, vehicle capacity and customer distribution. A heterogeneous electric vehicles routing and battery charging problem is presented with the consideration of differentiated service time. The problem is formulated as an integer programming model. Then, a heuristic MCWGATS and is proposed to solve the problem. MCWGATS is composed of four parts:modified Clark and Wright saving algorithm, hybrid genetic algorithm, local search and tabu search. The modified savings mechanism is used to optimize the service routes in the path subproblem. And then hybrid genetic algorithm is proposed to get assignment strategies. Finally, current strategy is optimized by LS and TS. Compared with the MIP solver of CPLEX on small-size instances, MCWGATS can solve the problem within a shorter computing time and get reasonable solutions. Then, parameter analysis of heterogeneous vehicles and differentiated service time is systematically conducted for this problem. The results show that the model contributes to help logistics firms to improve the utilization efficiency of such resources as staff, electric vehicles, service time, etc.

Key words: electricvehicles, heterogeneous vehicle routing problem, hybrid heuristic algorithm, differentiated service time, staff assignment problem