optimization

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

    A simulation framework for Formula 1 race strategy based on pit-stop optimization

  • Mario Borruso
  • Pasquale Avella
  • mattia_marino
    • Categories (Mixed) Integer Linear Programming, Linear Programming, Optimization Software and Modeling Systems Tags , , , ,

    In modern Formula~1, strict regulations and highly optimized cars limit performance gains through hardware, increasing the importance of strategic decision-making. This work tackles the problem of computing a race strategy that minimizes total race time by jointly optimizing tire stints, compound selection, fuel load, and Energy Recovery System (ERS) deployment. We present a high-performance simulation … Read more

    Optimization in Theory and Practice

  • Stephen Wright
    • Categories Convex Optimization, Linear Programming, Unconstrained Optimization Tags , ,

    Algorithms for continuous optimization problems have a rich history of design and innovation over the past several decades, in which mathematical analysis of their convergence and complexity properties plays a central role. Besides their theoretical properties, optimization algorithms are interesting also for their practical usefulness as computational tools for solving real-world problems. There are often … Read more

    Discovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling

  • I. Esra Buyuktahtakin Toy
    • Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Meta Heuristics Tags , , , , , , ,

    TitleDiscovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling Authorsİbrahim Oğuz Çetinkaya^1; İ. Esra Büyüktahtakın^1*; Parshin Shojaee^2; Chandan K. Reddy^2 Affiliations^1 Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA^2 Department of Computer Science, Virginia Tech, Arlington, VA, USA Abstract: Our study contributes to the scheduling and combinatorial optimization … Read more

    MultiObjectiveAlgorithms.jl: a Julia package for solving multi-objective optimization problems

  • Oscar Dowson
  • Xavier Gandibleux
  • Gökhan Kof
    • Categories Multi-Criteria Optimization, Optimization Software and Modeling Systems Tags , , ,

    We present MultiObjectiveAlgorithms.jl, an open-source Julia library for solving multi-objective optimization problems written in JuMP. MultiObjectiveAlgorithms.jl implements a number of different solution algorithms, which all rely on an iterative scalarization of the problem from a multi-objective optimization problem to a sequence of single-objective subproblems. As part of this work, we extended JuMP to support vector-valued … Read more

    Gradient-Driven Solution Based on Indifference Analysis (GIA) for Scenario Modelling Optimization Problem

  • Vincent Yuansang Zha
    • Categories Applications - OR and Management Sciences, Finance and Economics, Nonlinear Optimization Tags , , ,

    This paper introduces an optimization technique for scenario modeling in uncertain business situations, termed the Gradient-Driven Solution Based on Indifference Analysis (GIA). GIA evolves the conventional methods of scenario planning by applying a reverse-strategy approach, where future financial goals are specified, and the path to attain these targets are engineered backward. It adopts economic concepts … Read more

    Equity-promoting Integer Programming Approaches For Medical Resident Rotation Scheduling

  • Karmel S. Shehadeh
  • Shutian Li
  • Frank E. Curtis
  • Beth Hochman
    • Categories Applications - OR and Management Sciences, Integer Programming, Multi-Criteria Optimization Tags , , ,

    Motivated by our collaboration with a residency program at an academic health system, we propose new integer programming (IP) approaches for the resident-to-rotation assignment problem (RRAP). Given sets of residents, resident classes, and departments, as well as a block structure for each class, staffing needs, rotation requirements for each class, program rules, and resident vacation … Read more

    Global Optimization of Non-Linear Systems of Equations by Simulating the Flight of a Projectile in the Conformational Space

  • Nick Harkiolakis
    • Categories Applications - Science and Engineering, Global Optimization, Nonlinear Optimization Tags , , , ,

    A new heuristic optimization algorithm is presented based on an analogy with the physical phenomenon of a projectile launched in a conformational space under the influence of a gravitational force. Its implementation simplicity and the option to enhance it with local search methods make it ideal for the optimization of non-linear systems of equations. The … Read more

    Robustness Analysis for Adaptive Optimization With Application to Industrial Decarbonization in the Netherlands

  • Justin Starreveld
  • Dick den Hertog
  • Jaron Davelaar
  • gregorbrandt
  • Nort Thijssen
    • Categories Applications - OR and Management Sciences, Energy, Robust Optimization Tags , , ,

    Robustness analysis assesses the performance of a particular solution under variation in the input data. This is distinct from sensitivity analysis, which assesses how variation in the input data changes a model’s optimal solution. For risk assessment purposes, robustness analysis has more practical value than sensitivity analysis. This is because sensitivity analysis, when applied to … Read more