Bi-Objective Vehicle Routing for Perishable Products Delivery With Consideration of Customers’ Priorities and Customized Delivery Time Windows

As fresh product e-commerce experiences exponential expansion, the delivery of fresh products which are perishable is becoming a large part of road freight transportation. Transporting perishable products is a challenging task as it is difficult to preserve their nutritional value and freshness. To keep the freshness of such products in delivery, efficient transportation is critical. Besides, customers nowadays attach more importance to service flexibility, which contributes to customer satisfaction and is highly valued by suppliers. However, the service flexibility was seldom addressed previously in the delivery of fresh products. In this paper, we study a vehicle routing problem faced by a supplier who delivers perishable products to customers. We consider the service flexibility of the supplier who offers different delivery modes associated with differentiated time windows to customers. The supplier aims to maximize both its profit and customer satisfaction, where the customer satisfaction is measured by the weighted average quality loss of perishable products during delivery. This bi-objective vehicle routing problem with different customer priorities and delivery time windows is structured as a bi-objective mixed-integer linear programming model. To obtain the Pareto frontier of the model, an adaptive large neighborhood search (ALNS) algorithm based on the $\varepsilon $ -constraint method and a multi-objective ALNS algorithm are developed with several improvement strategies proposed. The computational results conducted on modified Solomon’s instances validate the model and prove the efficiency of the algorithms. Sensitivity analysis of the problem and the algorithms provide some managerial insights.