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Today's fast linear algebra and numerical optimization tools have pushed the frontier of model predictive control (MPC) forward, to the efficient control of highly nonlinear and hybrid systems. The field of hybrid MPC has demonstrated that…

Optimization and Control · Mathematics 2020-05-11 Jia-Jie Zhu , Georg Martius

This paper presents PIQP, a high-performance toolkit for solving generic sparse quadratic programs (QP). Combining an infeasible Interior Point Method (IPM) with the Proximal Method of Multipliers (PMM), the algorithm can handle…

Optimization and Control · Mathematics 2023-09-18 Roland Schwan , Yuning Jiang , Daniel Kuhn , Colin N. Jones

This paper addresses the problem of robust control of a linear discrete-time system subject to bounded disturbances and to measurement and control budget constraints. Using Q-parameterization and a polytope containment method, we prove that…

Optimization and Control · Mathematics 2021-09-23 Antoine Aspeel , Kwesi Rutledge , Raphaël M. Jungers , Benoit Macq , Necmiye Özay

Inverse linear programming (LP) has received increasing attention due to its potential to generate efficient optimization formulations that can closely replicate the behavior of a complex system. However, inversely inferred parameters and…

Optimization and Control · Mathematics 2022-02-22 Zahed Shahmoradi , Taewoo Lee

In this paper, we consider the problem of distributed optimal control of linear dynamical systems with a quadratic cost criterion. We study the case of output feedback control for two interconnected dynamical systems, and show that the…

Optimization and Control · Mathematics 2012-04-18 Ather Gattami , Omid Khorsand

Indefinite quadratic programs (QPs) are known to be very difficult to be solved to global optimality, so are linear programs with linear complementarity constraints. Treating the former as a subclass of the latter, this paper presents a…

Optimization and Control · Mathematics 2025-03-18 Xinyao Zhang , Shaoning Han , Jong-Shi Pang

We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates design and operational phases, which are represented by a mixed-integer program and discounted-cost…

Optimization and Control · Mathematics 2024-03-25 Seth Brown , Saumya Sinha , Andrew J Schaefer

In this paper, we propose novel mixed-integer linear programming (MIP) formulations to model decision problems posed as influence diagrams. We also present a novel heuristic that can be employed to warm start the MIP solver, as well as…

Optimization and Control · Mathematics 2026-01-21 Helmi Hankimaa , Olli Herrala , Fabricio Oliveira , Jaan Tollander de Balsch

We study mixed-integer programming (MIP) relaxation techniques for the solution of non convex mixed-integer quadratically constrained quadratic programs (MIQCQPs). We present MIP relaxation methods for non convex continuous variable…

Optimization and Control · Mathematics 2023-08-21 Benjamin Beach , Robert Burlacu , Andreas Bärmann , Lukas Hager , Robert Hildebrand

For multiparametric mixed-integer convex programming problems such as those encountered in hybrid model predictive control, we propose an algorithm for generating a feasible partition of a subset of the parameter space. The result is a…

Optimization and Control · Mathematics 2019-03-01 Danylo Malyuta , Behcet Acikmese , Martin Cacan , David S. Bayard

Quadratic programming (QP) is a well-studied fundamental NP-hard optimization problem which optimizes a quadratic objective over a set of linear constraints. In this paper, we reformulate QPs as a mixed-integer linear problem (MILP). This…

Optimization and Control · Mathematics 2018-07-17 Wei Xia , Juan Vera , Luis F. Zuluaga

In recent years, numerous vision and learning tasks have been (re)formulated as nonconvex and nonsmooth programmings(NNPs). Although some algorithms have been proposed for particular problems, designing fast and flexible optimization…

Computer Vision and Pattern Recognition · Computer Science 2017-07-03 Yiyang Wang , Risheng Liu , Xiaoliang Song , Zhixun Su

A standard quadratic program is an optimization problem that consists of minimizing a (nonconvex) quadratic form over the unit simplex. We focus on reformulating a standard quadratic program as a mixed integer linear programming problem. We…

Optimization and Control · Mathematics 2018-10-05 Jacek Gondzio , E. Alper Yildirim

This paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programming (PQP) through dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data…

Systems and Control · Electrical Eng. & Systems 2019-11-26 Kooktae Lee

Achieving optimal steady-state performance in real-time is an increasingly necessary requirement of many critical infrastructure systems. In pursuit of this goal, this paper builds a systematic design framework of feedback controllers for…

Optimization and Control · Mathematics 2017-10-30 Zachary E. Nelson , Enrique Mallada

Hybrid optimal control problems are studied for a general class of hybrid systems where autonomous and controlled state jumps are allowed at the switching instants and in addition to terminal and running costs switching between discrete…

Optimization and Control · Mathematics 2017-02-22 Ali Pakniyat , Peter E. Caines

We present a hybrid control framework for solving a motion planning problem among a collection of heterogenous agents. The proposed approach utilizes a finite set of low-level motion primitives, each based on a piecewise affine feedback…

Systems and Control · Computer Science 2017-07-24 Marijan Vukosavljev , Zachary Kroeze , Mireille E. Broucke , Angela P. Schoellig

This paper proposes a quantum framework for the design of communication topologies in consensus-based multi-agent systems. The communication graph is selected online by solving a mixed-integer quadratic program (MIQP) that minimizes a cost…

Systems and Control · Electrical Eng. & Systems 2026-02-09 Milad Hasanzadeh , Amin Kargarian

This work presents a hybrid approach to solve the maximum stable set problem, using constraint and semidefinite programming. The approach consists of two steps: subproblem generation and subproblem solution. First we rank the variable…

Combinatorics · Mathematics 2007-05-23 W. J. van Hoeve

We present a technique for producing valid dual bounds for nonconvex quadratic optimization problems. The approach leverages an elegant piecewise linear approximation for univariate quadratic functions due to Yarotsky, formulating this…

Optimization and Control · Mathematics 2021-03-30 Ben Beach , Robert Hildebrand , Joey Huchette