A Container Vehicle Routing Model with Variable Traveling Time

Vehicle traveling time is vital for vehicle routing problem. Due to traffic, jam, et al, it generally varies with different times of day, traffic conditions and so on. Considering simultaneous pick-up and delivery service, this paper aims to solve a local container vehicle routing problem with variable traveling time faced by container terminal and forwarders. A genetic algorithm (GA) is advanced to gain an efficient and feasible solution by improving solution encoding, GA operators and involution strategy. Experiments show that the proposed model and algorithm are potentially efficient and useful in solving container vehicle routing problems with variable traveling time in acceptable CPU time.