Research On Take-out Delivery Routing Problem With Uncertain Factors

With the rapid development of catering O2O,take-out food has changed people’s traditional catering consumption pattens.As the core link of the operation of the third-party take-out platform,the reasonable delivery route has a great influence on the distribution efficiency,platform operation costs and customer satisfaction.In such a fierce competition in the take-out market,scientific reasonable methods to optimize the size of the distribution team and delivery routes,control logistics costs and improve operating efficiency under the premise of ensuring service quality are the keys to the sustainable development of third-party take-out platforms.This paper studies the related problems of take-out distribution,the take-out delivery-routing problem with uncertain factors is proposed.Based on the full consideration of the special nature of take-out food,studies the description of delivery scenario according to the background of practical problems and the characteristics of the take-out distribution.From the perspective of the economic benefits of the third-party take-out platform,considering the distribution cost,order commission and penalty costs that violate the time windows,a mixed integer programming model is constructed with the objective of minimizing the total operation costs.At the same time,the Monte Carlo simulation method is used to introduce stochastic travel time into the model.According to the characteristics of the model,a tabu search algorithm that matches the problem is designed to solve the proposed problem,and the model and algorithm are verified by the experiments,which can be used to get the delivery routing selection scheme in the real situation.On the basis of considering the economic benefits of the third-party take-out platform and stochastic travel time,in order to make full use of the distribution personnel resources,time benefit is also introduced,considering the time of the delivery and the waiting time for staff to pick up the take-out food.Simultaneously optimize and balance the two objective functions of economic benefits and time benefits,and construct a multi-objective optimization model.According to the characteristics of the problem and the model,an elitist non-dominated sorting genetic algorithm(NSGA-Ⅱ)is designed.Comparative results and statistical analysis show the effectiveness of the model and algorithm which can provide decision support for third-party take-out platforms scheduling optimization.The Pareto optimal solution provides more decision-making options for the third-party platform managers.