Applications – OR and Management Sciences

Optimality Gap of Tailored Base-Surge Policies Decays Exponentially in Regular-Source Lead Times for Dual-Sourcing Models

  • Xin Chen
  • Shuai Li
  • Weijun Xie
    • Categories Dynamic Programming, Stochastic Programming, Supply Chain Management Tags , , , , ,

    This paper resolves an open problem posed in the literature by proving that, in dual-sourcing inventory systems, the optimality gap of tailored base-surge (TBS) policies decays exponentially with the regular source lead time, with the express-source lead time fixed. In contrast to the existing approach, which relies on conditional Jensen inequalities and a vanishing-discount argument … Read more

    Betweenness Central Nodes Under Uncertainty: An Absorbing Markov Chain Approach

  • Wencheng Bao
  • Eleftheria Kontou
  • Chrysafis Vogiatzis
    • Categories Applications - OR and Management Sciences, Applications - Science and Engineering, Robust Optimization Tags , , , , , , ,

    We propose a betweenness centrality measure and algorithms for stochastic networks, where edges can fail and weights vary across realizations, making the most central node random. Our approach models the sequence of reported central nodes as an absorbing Markov chain and measures node importance by the share of pre-absorption time spent at each node. This … Read more

    Supervised feature selection via multiobjective programming and its application in the medical field

  • Pham Thi Hoai
    • Categories Applications - OR and Management Sciences, Constrained Nonlinear Optimization, Convex and Nonsmooth Optimization, Convex Optimization, Other Topics Tags , , , ,

    In this study, we model the supervised feature selection problem using a novel approach: convex bi-objective optimization. Traditional methods have addressed this problem by maximizing relevance to class labels and minimizing redundancy among features. Recently, Wang et al. [30] formulated this problem as a single-objective convex optimization, yielding only a unique solution. Unlike that, we … Read more

    The Distributionally Robust Cyclic Inventory Routing Problem

  • Menglei Jia
  • Albert H. Schrotenboer
  • Ahmadreza Marandi
  • chernfeng
    • Categories Production and Logistics, Supply Chain Management, Transportation Tags , , ,

    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

    Finite-Sample Optimality and Constraint Satisfaction: Learning-Based Optimal Control in Dynamic Dispatch Networks

  • Moustafa Rashidy
    • Categories Data Science Theory, Production and Logistics, Transportation Tags , ,

    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

    Rethinking Last-Mile Routing at Scale: Near-Linear Planning on Commodity Hardware

  • Martin Vizzolini
    • Categories Optimization Software and Modeling Systems, Production and Logistics, Supply Chain Management Tags , , , , , , , , , , , , , ,

    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

    Reverse stress testing for supply chains

  • Busra Gultekin
  • Frans J.C.T. de Ruiter
  • Meike Reusken
  • Sander de Leeuw
    • Categories Applications - OR and Management Sciences, Integer Programming, Supply Chain Management Tags , , ,

    This study introduces reverse stress testing for supply chains, designed to identify the minimal deviations from normal operations that would drive supply chains to a predefined performance failure. First, we present a framework for reverse stress testing with the purpose of assessing supply chain vulnerabilities. The framework involves six steps: selecting risk variables, defining baselines, … Read more

    Pricing Discrete and Nonlinear Markets With Semidefinite Relaxations

  • Cheng Guo
  • Lauren Henderson
  • Ryan Cory-Wright
  • Boshi Yang
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Semi-definite Programming Tags , , , ,

    Nonconvexities in markets with discrete decisions and nonlinear constraints make efficient pricing challenging, often necessitating subsidies. A prime example is the unit commitment (UC) problem in electricity markets, where costly subsidies are commonly required. We propose a new pricing scheme for nonconvex markets with both discreteness and nonlinearity, by convexifying nonconvex structures through a semidefinite … Read more

    An Interpretable Ensemble Heuristic for Principal-Agent Games with Machine Learning

  • I. Esra Buyuktahtakin Toy
    • Categories Applications - OR and Management Sciences, Game Theory, Optimization in Data Science

    This paper addresses the challenge of enhancing public policy decision-making by efficiently solving principal-agent models (PAMs) for public-private partnerships, a critical yet computationally demanding problem. We develop a fast, interpretable, and generalizable approach to support policy decisions under these settings. We propose an interpretable ensemble heuristic (EH) that integrates Machine Learning (ML), Operations Research (OR), … Read more

    On the Single-Multi-Commodity Gap: Lifting Single- to Multicommodity Flow Instances

  • Felix P. Broesamle
  • Stefan Nickel
    • Categories Applications - OR and Management Sciences, Linear Programming, Network Optimization Tags , , , , ,

    Benchmark instances for multicommodity flow problems frequently lack the structural nuances of real-world networks or fail to maintain a rigorous mathematical relationship with their single-commodity counterparts. This paper introduces a formal meta-generation framework that addresses these limitations by lifting single-commodity minimum-cost flow instances into the multicommodity space while strictly preserving the underlying network topology, capacity … Read more