Month: April 2025

Mathematical programs with complementarity constraints and application to hyperparameter tuning for nonlinear support vector machines

  • Samuel Ward
  • Alain Zemkoho
  • Selin Damla Ahipasaoglu
    • Categories Bilevel Optimization, Complementarity and Variational Inequalities, Optimization in Data Science Tags , , , , ,

    We consider the Mathematical Program with Complementarity Constraints (MPCC). One of the main challenges in solving this problem is the systematic failure of standard Constraint Qualifications (CQs). Carefully accounting for the combinatorial nature of the complementarity constraints, tractable versions of the Mangasarian Fromovitz Constraint Qualification (MFCQ) have been designed and widely studied in the literature. … Read more

    An interactive optimization framework for incorporating a broader range of human feedback into stochastic multi-objective mixed integer linear programs

  • Damsara Jayarathne
  • Jennifer Pazour
  • John E. Mitchell
    • Categories (Mixed) Integer Linear Programming, Multi-Criteria Optimization, Stochastic Programming Tags , , , ,

    Interactive optimization leverages the strengths of optimization frameworks alongside the expertise of human users. Prior research in this area tends to either ask human users for the same type of information, or when varying information is requested, users must manually modify the optimization model directly. These limitations restrict the incorporation of wider human knowledge into … Read more

    Pareto Leap: An Algorithm for Biobjective Mixed-Integer Programming

  • Philip de Castro
  • Margaret Wiecek
    • Categories (Mixed) Integer Nonlinear Programming, Integer Programming, Multi-Criteria Optimization Tags , , ,

    Many real-life optimization problems need to make decisions with discrete variables and multiple, conflicting objectives. Due to this need, the ability to solve such problems is an important and active area of research. We present a new algorithm, called Pareto Leap, for identifying the (weak) Pareto slices of biobjective mixed-integer programs (BOMIPs), even when Pareto … Read more

    Globally Converging Algorithm for Multistage Stochastic Mixed-Integer Programs via Enhanced Lagrangian Cuts

  • Hanbin Yang
  • Haoxiang Yang
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , ,

    This paper proposes a globally converging cutting-plane algorithm for solving multistage stochastic mixed-integer programs with general mixed-integer state variables. We demonstrate the generation process of Lagrangian cuts and show that Lagrangian cuts capture the convex envelope of value functions on a restricted region. To approximate nonconvex value functions to exactness, we propose to iteratively add … Read more

    Superiorization and Perturbation Resilience of Algorithms: A Continuously Updated Bibliography

  • Yair Censor
    • Categories Applications - Science and Engineering, Constrained Nonlinear Optimization Tags , , ,

    This document presents a (mostly) chronologically-ordered bibliography of scientific publications on the superiorization methodology and perturbation resilience of algorithms which is compiled and continuously updated by us at: http://math.haifa.ac.il/yair/bib-superiorization-censor.html. Since the beginnings of this topic we try to trace the work that has been published about it since its inception. To the best of our … Read more

    A characterization of positive spanning sets with ties to strongly edge-connected digraphs

  • Denis Cornaz
  • Sébastien Kerleau
  • Clément W. Royer
    • Categories Graphs and Matroids, Nonlinear Optimization, Unconstrained Optimization

    Positive spanning sets (PSSs) are families of vectors that span a given linear space through non-negative linear combinations. Despite certain classes of PSSs being well understood, a complete characterization of PSSs remains elusive. In this paper, we explore a relatively understudied relationship between positive spanning sets and strongly edge-connected digraphs, in that the former can … Read more

    A 2-index Stage-based Formulation and a Construct-Merge-Solve & Adapt Algorithm for the Flying Sidekick Traveling Salesman Problem

  • khanhhbk4a10
    • Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Meta Heuristics

    In this work, we present the first 2-index stage-based formulation for the Flying Sidekick Traveling Salesman Problem (FSTSP). Additionally, we propose a Construct-Merge-Solve & Adapt (CMSA) algorithm designed to generate high-quality feasible solutions. Experimental results demonstrate that the proposed algorithm consistently produces good solutions in a fraction of the time required by state-of-the-art mixed-integer linear … Read more

    Recursive Partitioning and Batching for Network Design with Service Time Guarantees at Massive Scale

  • Myungeun Eom
  • Alan L. Erera
  • Alejandro Toriello
    • Categories Production and Logistics, Supply Chain Management, Transportation Tags , , , ,

    Motivated by the parcel delivery industry, we study a network design problem with service time guarantees at industrial scale. This tactical service network design problem determines primary paths and delivery schedules for commodities to minimize transportation and handling costs while ensuring committed service times. To construct a solution for a real-world instance with over 1,000 … Read more

    Tight Semidefinite Relaxations for Verifying Robustness of Neural Networks

  • Godai Azuma
  • Sunyoung Kim
  • Makoto Yamashita
    • Categories Optimization in Data Science, Quadratic Programming, Semi-definite Programming Tags , , , ,

    For verifying the safety of neural networks (NNs), Fazlyab et al. (2019) introduced a semidefinite programming (SDP) approach called DeepSDP. This formulation can be viewed as the dual of the SDP relaxation for a problem formulated as a quadratically constrained quadratic program (QCQP). While SDP relaxations of QCQPs generally provide approximate solutions with some gaps, … Read more

    A relaxed version of Ryu’s three-operator splitting method for structured nonconvex optimization

  • Felipe Atenas
  • Jan Harold Alcantara
    • Categories Nonlinear Optimization, Nonsmooth Optimization

    In this work, we propose a modification of Ryu’s splitting algorithm for minimizing the sum of three functions, where two of them are convex with Lipschitz continuous gradients, and the third is an arbitrary proper closed function that is not necessarily convex. The modification is essential to facilitate the convergence analysis, particularly in establishing a … Read more