Delivering fresh produce during a lockdown: The post-pandemic pickup and distribution problem with time constraints

Motivated by the logistical challenges of distributing fresh produce during prolonged, government-enforced lockdowns, we investigate a novel problem: the Post-Pandemic Pickup and Distribution Problem with Time Constraints (PP-PDPTC). In the post-pandemic phase, supply and demand stabilize, yet food distribution remains constrained by rigid time windows and institutional rules. This setting requires a careful balance of effectiveness (demand fulfilment), equity (fair distribution), and efficiency (timely delivery). We propose two models for equity-aware food allocation. The first assumes that decision-makers possess prior knowledge of acceptable inequality levels (e.g., a maximum Gini coefficient) and treats equity as a constraint; the second embeds equity directly in the objective function, enabling dynamic trade-offs. We further devise a Transfer and Deprivation strategy that reallocates surplus food from overserved areas or trims excess allocations to improve equity. Coupled with an Adaptive Large Neighborhood Search algorithm for routing, this yields a two-stage heuristic framework. We test the models on a real-world case from Shanghai's Omicron lockdown in March 2022. Results reveal key trade-offs: pursuing equity can raise food waste under oversupply, increasing fleet size chiefly boosts effectiveness, whereas expanding vehicle capacity benefits equity. The heuristic consistently surpasses commercial solvers in solution quality and runtime, offering a practical tool for post-pandemic fresh-produce distribution under institutional constraints.