Admission and Assortment Optimization for Multi-size Automated Parcel Lockers

We study admission control and capacity design for automated parcel lockers with multiple parcel and locker sizes.

A smaller parcel can use a larger locker, but doing so may block a future larger parcel whose rejection is more costly.

We formulate the admission problem as a finite-state, infinite-horizon average-cost Markov decision process and solve small instances exactly by relative value iteration.

We analyze the always-accept (AA) policy, which admits every feasible parcel into the remaining compatible capacity, and give a sufficient condition for its optimality.

Across two-, three-, and four-size experiments, AA is optimal in fast-pickup regimes and nearly optimal when holding times are longer; observed optimality gaps are negligible even when AA is not optimal.

We then study the locker-assortment problem, which minimizes facility cost plus optimal expected rejection cost.

We give an exact bound-and-enumerate algorithm for moderate-size instances.

Although the objective is not discrete convex, exchange-neighborhood local search finds the certified optimum in every instance for which exact certification is computationally tractable, and it scales as a heuristic to larger systems.