Intelligent Vehicle Scheduling with Soft Time Window and Non-full Load Constraint

Abstract

Vehicle scheduling belongs to a typical TSP (Traveling salesman problem) problem in the field of combinatorial optimization. We design a vehicle scheduling model with soft time window and non-full load constraints. The model belongs to single-objective optimization with multiple constrains. This article uses binary particle swarm optimization algorithm (BPSO) to solve the vehicle scheduling model, combining constraint deviation value method for solving constraint. Cross experiments are designed based on the number of customers and the number of delivery vehicles. The experiment results show that BPSO algorithm in short running time can resolve vehicle scheduling problem, and get a more satisfactory solution to objective function, the number of vehicles customers required, the distribution distance and path of the delivery vehicle. Thus it lays a technical foundation for intelligent vehicle scheduling.