For integer activities, conditioning on the support makes a fixed-charge objective affine. If every support-conditioned cell is integral, an optimal solution is a vertex of its cell for arbitrary fixed charges and marginal rates. A totally unimodular constraint matrix with integral data guarantees this condition. This surviving property is weaker than the classical conclusions. A … Read more
Many retail distribution networks use a hierarchical structure in which regional distribution centers replenish local distribution centers that are closer to customers. In such networks, products are often shipped in large quantities, as case packs, cases or pallets, to the regional distribution center, whereas local distribution centers may require quantities at the individual-unit level. Case … Read more
Residential parcel lockers (RPLs), unlike their public counterparts, facilitate secure parcel delivery to occupants of private apartment and condominium buildings in urban areas. In this work, we consider the perspective of a last-mile parcel carrier that has access to an RPL in the lobby of a high-rise residential building. Motivated by growing e-commerce demand, we … Read more
The diverse constraints of industrial applications lead to variants of two-dimensional (2D) irregular packingproblems that require tailored solution methods. This paper addresses a real-world industrial challenge byproposing a new problem definition, the maximum reusable contiguous area problem (MRCAP), and a novelmetric, the maximum contiguous area, to measure and maximize the contiguous unused area in a … Read more
We study the cyclic inventory routing problem that involves joint decisions on vehicle routing and inventory replenishment on an infinite, cyclic horizon. It considers a single warehouse and a set of geographically dispersed retailers. We model retailer demand as random variables with uncertain distributions belonging to a moment-based ambiguity set. We develop a distributionally robust … Read more
Dynamic dispatch networks in logistics and transportation require real-time, constraint-aware decision-making under stochastic demand. This paper bridges mathematical optimization, optimal control theory, and reinforcement learning by establishing non-asymptotic theoretical guarantees for learning-based optimal control in constrained stochastic dispatch systems. We formulate the problem as a constrained Markov decision process, enforce feasibility via a projection-based policy … Read more
This paper presents a practical architecture for last-mile delivery routing at scales reaching one million stops under realistic operational conditions, including vehicle capacity, package volume, route stop limits, and time windows. Unlike conventional systems that require pre-partitioning or large-scale infrastructure, the proposed system addresses the full fleet planning problem through a single coherent planning pipeline … Read more
We study a continuous-time pump scheduling problem for a flow transmission task. A finite table of empirical operating points of pump combinations is given, each point specifying a flow rate and power consumption. Electricity prices follow a time-of-use tariff, and combination changes are penalized or limited by per-shift switch caps. We prove a structural theorem: … Read more
We study the tactical problem of determining a last-mile delivery fleet size while accounting for day-to-day uncertainty in the number and location of customer requests. An optimally sized fleet must balance the cost of contracting vehicles against the penalty costs of unserved customers: a larger fleet reduces the risk of unserved demand, but a smaller … Read more
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