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 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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Public school bus routes can change from year to year as students and their home locations change. However, school administrators benefit from the ability to predict future transportation needs on multi-year time scales. With this motivation in mind, this paper develops planning models for school bus routing when student locations are not known with certainty. … Read more
This paper addresses an operational planning challenge in two-tier robotized sorting systems (T-RSS), an emerging alternative to traditional conveyor-based sorting in e-commerce delivery stations. Designed to be compact and space-efficient, T-RSS use an upper tier to sort parcels from loading stations to drop-off points, which connect to roll containers on a lower tier where parcels … Read more
This paper proposes a mixed-integer nonlinear programming approach for joint scheduling of long-term maintenance decisions and short-term production for groups of complex machines with multiple interacting components. We introduce an abstract model where the production and the condition of machines are described by convex functions, allowing the model to be employed for various application areas … Read more
We introduce the Expeditionary Logistics Network Design Problem (ELNDP), a new formulation for operational-level planning in expeditionary environments where multi-modal vehicle coordination is critical and penalties for unmet demand dominate transportation costs. ELNDP extends the classical Scheduled Service Network Design Problem by incorporating flexible commodity sourcing and heterogeneous vehicle capabilities, both essential in military logistics. … Read more
We consider a dynamic lot sizing model in which end products to satisfy demands are obtained by remanufacturing m core types of differing quality, where m ≥ 1, or manufacturing from raw materials. In the model, we have separate setup costs associated with manufacturing and remanufacturing. As is widely known, remanufacturing is an environmental preferable … Read more