Last-mail Location-routing Optimization With Split Demand For Customer Self-pickup

Customer self-pickup,offered as an option at most distribution centers,can provide flexible service times and save operational costs.Customers can either choose to self-pickup their demand or to have it delivered by a traditional way.At each customer point,the delivery demand is split,with the amount depending on the service and personal characteristics.In case of variable demand,how to efficiently locate distribution centers and route deliveries becomes a vital problem for express companies that has not been studied in the literature.In this paper,for the first time,we propose a mathematical programming model for optimizing the location-routing problem with split demand(LRP-SD),allowing vehicles to be delivered multiple times,together with a delivery ratio analysis model to predict self-pickup and delivery demand.To adapt the model to real-world cases,two heuristics as used in large-scale simulation-based optimization are devised and implemented.One is biogeography-based optimization(BBO)for solution speed,and the other is an adaptive large neighborhood search(ALNS)for solution quality.The two algorithms are compared using real data from a Shanghai-based express delivery company in terms of performance.The case results verify that the location-routing problem with customer's demand split,which can effectively reduce the last-mail logistics cost,improve the vehicle utilization rate to some extent,change the location decision,reduce the number of delivery vehicles and re-plan the vehicle routing.