Early Termination of Convex QP Solvers in Mixed-Integer Programming for Real-Time Decision Making

The branch-and-bound optimization algorithm for mixed-integer model predictive control (MI-MPC) solves several convex quadratic program relaxations, but often the solutions are discarded based on already known integer feasible solutions. This letter presents a projection and early termination strate...

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Bibliographic Details
Published in:IEEE control systems letters Vol. 5; no. 4; pp. 1417 - 1422
Main Authors: Liang, Jiaming, Cairano, Stefano Di, Quirynen, Rien
Format: Journal Article
Language:English
Published: IEEE 01.10.2021
Subjects:
Cyber-physical systems
Decision making
mixed-integer programming
Numerical simulation
Optimization
optimization algorithms
Prediction algorithms
Predictive control
Programming
Real-time systems
ISSN:2475-1456, 2475-1456
Online Access:Get full text
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Summary:The branch-and-bound optimization algorithm for mixed-integer model predictive control (MI-MPC) solves several convex quadratic program relaxations, but often the solutions are discarded based on already known integer feasible solutions. This letter presents a projection and early termination strategy for infeasible interior point methods to reduce the computational effort of finding a globally optimal solution for MI-MPC. The method is shown to be also effective for infeasibility detection of the convex relaxations. We present numerical simulation results with a reduction of the total number of solver iterations by 42% for an MI-MPC example of decision making for automated driving with obstacle avoidance constraints.
ISSN:2475-1456
2475-1456
DOI:10.1109/LCSYS.2020.3038677