Vehicle scheduling problems of military logistics distribution based on improved Genetic Algorithm

This paper is aimed to research into military vehicle scheduling problem (VSP) using Genetic Algorithm. By shifting the constrain conditions of delivery time windows and vehicle capacities to objective function, A vehicle scheduling model was built up based on the objective of minimum length of total transportation distance, which included penalty function terms of time window and vehicle capacity constrains, and the model characteristics and application prospects was analyzed. To solve the model, a improved Genetic Algorithm program was put forward, in which a chromosome coding suitable to describe delivery routes was designed, a suitable-degree function was proposed, and a reproduction operator, a crossover operator and a mutation operator were constructed. An example was given to demonstrate feasibility and actual application method of the model and algorithm program. The study indicates that the Genetic Algorithm program has higher algorithm efficiency and can effectively solve vehicle scheduling problems of military distribution centers; The parameter selection of the algorithm significantly influences the algorithm convergence.