Research on Retail Logistics Collaborative Scheduling Optimization Considering Differentiated Service Time
The epidemic has accelerated the expansion of traditional retailers to online businesses and the emer-gence of new retail models integrating online and offline,making the timeliness of retail logistics and service quality the key to winning the market in the post-epidemic era.Under the new retail model,the logistics demands of consumers are more dispersed and the batch frequency is higher.Different orders and logistics distribution need to be uniformly deployed,which puts forward higher requirements for the service quality and timeliness of logistics distribution.Retail logistics distribution service requires the cooperation among logistics personnel,distribution vehicles and customers,ignoring the differentiated service time of logistics personnel,the different departing time of vehicles due to different release dates,and the timeliness of customer demand lead to high cost,poor timeliness and low customer satisfaction of retail logistics distribution schemes.When logistics personnel are familiar with the surrounding environment of customers,they can quickly and accurately find the distribution address and appropriate parking points,and even get familiar with the traffic conditions to avoid the congested sections.Especially in the post-epidemic era,the epidemic situation presents a multi-point distribution state,customer demands are scattered and change every day,and logistics distribution personnel are also absent due to temporary lockdown.If differentiated service time is ignored,this will not be conducive to the full utiliza-tion of human resources,or to the response to emergencies.Order release dates determines the vehicle departure and distribution time,which not only affects the collaborative decision of order assignment and route planning,but also has an important impact on distribution efficiency.In addition,as the distribution process is often accompanied by force majeure factors such as bad weather and traffic jams,the customer delivery time window is usually flexible,which means that the customer is allowed to receive the service earlier or later than the specified time window to a certain extent,but the violation of the specified time window will lead to the decline of customer satisfaction,so the corresponding punishment is considered in the objective function.In this context,we study the collaborative scheduling problem of retail logistics aiming to minimize travel cost,penalty cost and differentiated service time cost.Under the constraints of order release dates and customer flexible time window,dispatching a group of logistics distribution personnel to complete the delivery tasks of customer orders is a collaborative optimization of task assignment and vehicle routing planning for multiple logistics distribution personnel with differentiated service time.To solve this problem,a linear mathematical programming model is established with the optimization objective,and the improved iterated local search algorithm based on large neighborhood search process is designed in this paper.This algorithm uses regret repair operator to generate high quality initial solution to enhance the search efficiency,and introduces large neighborhood search with four removal operators and two repair operators,a breaking mechanism and optimal service start time model to enhance the global optimal search ability of the algorithm.Finally,the numerical experiment verifies the effectiveness of the model and algorithm by solving bench-marking instances and the numerical instances in the paper,and the sensitivity analysis of the parameters gives corresponding management enlightenment,which provides effective reference and suggestions for the effective management of distribution personnel,efficiency improvement of distribution and cost control of retail logistics operation management in the post-epidemic era.
retail logisticsdifferentiated service timerelease datescollaborative optimization
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