Multi-Objective Optimization Method For Vehicle Scheduling With Alternative Time Windows

In the actual vehicle scheduling problem,the vehicle scheduling multi-objective optimization problem with alternative time windows is a common problem.Because the existed research does not involve optional time windows,it is necessary to conduct research and propose effective methods to solve this type of problem.Aiming at the single distribution center vehicle scheduling optimization problem with alternative time windows,a multi-objective optimization model with the lowest total distribution cost and the highest average customer satisfaction was constructed and a non-dominated sorting genetic algorithm(NSGA Ⅱ)was designed to solve it.In the algorithm,an integer coding method was adopted to encode individuals.A rejection strategy was used in population initialization to ensure the feasibility of each individual.An improved strategy of genetic operator was adopted in genetic operation to ensure the feasibility of coding.A rejection strategy was used to ensure each route can select available vehicle type.In decode operation,customer satisfaction was calculated by the customer delivery time of goods under each time window.Customer satisfaction was the maximum of each customers satisfactions.Average customer satisfaction was the average of satisfactions of all customers.Shunting cost and transport cost were calculated according to the individual’s coding,Total delivery cost was the sum of shunting cost and transport cost.On multi-distribution center problem,Turning the multi-distribution center problem into single distribution center problem through Merge Optimization Algorithm.The case study indicated that the proposed method can efficiently solve the single distribution center vehicle scheduling multi-objective optimization problem with alternative time windows.Aiming at the multi distribution center vehicle scheduling optimization problem with alternative time windows,a multi-objective optimization model with the lowest total distribution cost and the highest average customer satisfaction was constructed and Merge Optimization Algorithm was designed for partition processing.The multi-distribution center problem was transformed into a single-distribution center problem for solution.The case study indicated that the proposed method can efficiently solve the multi distribution center vehicle scheduling multi-objective optimization problem with alternative time windows.