Integrated differentiated time slot pricing and order dispatching with uncertain customer demand in on-demand food delivery

Differentiated time slot pricing (DTSP) is a promising approach to enhance the efficiency and cost-effectiveness of food delivery platforms by influencing customers’ choices regarding delivery time slots. In this paper, we investigate the integrated problem of DTSP at the tactical level and order dispatching at the operational level, formulating it as a two-stage stochastic programming model. The first-stage model determines the delivery price for each time slot to maximize the system’s expected profit. The second-stage model generates the optimal order dispatching plan to minimize the generalized system cost under each stochastic scenario. To efficiently estimate the order dispatching cost for each scenario, we develop an order consolidation dispatching algorithm (OCDA) to solve the second-stage order dispatching subproblem under each demand scenario. Building on OCDA, we propose a hybrid adaptive large neighborhood search (HALNS) heuristic to solve the integrated problem. Extensive case studies based on real-world data verify the effectiveness of the proposed approach and demonstrate the benefits of DTSP strategy. Our numerical analysis provides important managerial insights for operating food delivery platforms.