Constrained optimization as ecological dynamics with applications to random quadratic programming in high dimensions

Pankaj Mehta, Wenping Cui, Ching-Hao Wang, and Robert Marsland, III
Phys. Rev. E 99, 052111 – Published 13 May 2019

Abstract

Quadratic programming (QP) is a common and important constrained optimization problem. Here, we derive a surprising duality between constrained optimization with inequality constraints, of which QP is a special case, and consumer resource models describing ecological dynamics. Combining this duality with a recent “cavity solution,” we analyze high-dimensional, random QP where the optimization function and constraints are drawn randomly. Our theory shows remarkable agreement with numerics and points to a deep connection between optimization, dynamical systems, and ecology.

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  • Received 29 October 2018

DOI:https://doi.org/10.1103/PhysRevE.99.052111

©2019 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsPhysics of Living Systems

Authors & Affiliations

Pankaj Mehta1,*, Wenping Cui1,2, Ching-Hao Wang1, and Robert Marsland, III1

  • 1Physics Department, Boston University, Boston, Massachusetts 02215, USA
  • 2Physics Department, Boston College, Chestnut Hill, Massachusetts 02467, USA

  • *pankajm@bu.edu

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Vol. 99, Iss. 5 — May 2019

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