Real-time Pick-up and Delivery Problem Based on Customer Satisfaction
With the rapid development of takeout industry,the time and scale of distribution are continuously improved,which makes the traffic violations such as retrograde motion and over speed increase sharply.The rapid development of takeout industry also makes takeout platforms and restaurateurs pay more and more attention to customer satisfaction,further reduces the distribution time which directly relates to customer satisfaction.O2O takeout platforms use the straight-line distance to estimate the delivery time,but the transportation network of urban business district actually has an asymmetric structure.Therefore,the distribution problem considering customer satisfaction and actual distribution network has become an important research problem of terminal real-time distribution.Based on the actual distribution network,the paper explores the optimization of real-time pick-up and delivery path considering customer satisfaction.In view of the real-time and difference of customers'orders,distribution vehicles are required to adjust the distribution path and determine whether to return to the origin.The real-time pick-up and delivery path optimization problem considering customer satisfaction is studied.Softtime window constraints are added to characterize customer satisfaction and a real-time pick-up and delivery path optimization model considering customer satisfaction is established.By defining and adjusting the asymmet-ric network coefficients,the asymmetric distribution network is constructed;the Ignore strategy and Real-time strategy are proposed.The Ignore strategy requires the deliveryman to ignore all new orders before returning to the distribution starting point.The Real-time strategy requires the deliveryman to judge in real-time whether to return to the starting point to pick up goods and re-plan the distribution route when new orders appear.Using the numerical simulation software and calling the genetic algorithm,the applicability of the two strategies is analyzed under different network sizes,rolling time domain duration,asymmetric coefficient,time windows and order quantity.The numerical example analysis shows that the Real-time strategy is more suitable for the case of larger network,while the Ignore strategy will be more suitable when the network is smaller and the number of orders is fewer.When the network is large,as the asymmetric coefficient increases,the number of times the cost mean of the Real-time strategy is lower than the cost mean of the Ignore strategy will gradually decrease.As the number of orders increases,the number of times the average cost of the Real-time strategy is lower than the average cost of the Ignore strategy will gradually increase.When the network is small,this trend will be exactly the opposite as the asymmetry coefficient and order quantity increase.Will the dynamic release characteristics of orders have a significant impact on actual delivery costs?Will the asymmetry of distribution networks,which has a significant impact on distribution costs,be considered?On the premise of not affecting customer purchasing behavior,different delivery times can be promised to customers when there are significant differences in order distribution.This paper is based on asymmetric networks and studies the real-time pickup and delivery path optimization problem based on customer time windows.Online algorithms are designed and mathematical models are built to study the problem.In the future,further optimization of the research object and background can be achieved.The scenario considered in this article is bicycles,a single type of customer.Future research can classify custom-er types based on customer value or the value of delivered goods,and use multiple vehicles for delivery,making it more relevant to the real background.The setting of asymmetric network coefficients in the case analysis is too singular.In the future,random functions can be used to set different parameter value.
traveling salesman problemcombined shippingreal-time pick-up and deliveryunilateral soft time windowasymmetrical networks for different paths
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