4 papers
Parallel Domain-Decomposition Algorithms for Complexity Certification of Branch-and-Bound Algorithms for Mixed-Integer Linear and Quadratic Programming
Shamisa Shoja, Daniel Arnström, Daniel Axehill
When implementing model predictive control (MPC) for hybrid systems with a linear or a quadratic performance measure, a mixed-integer linear program (MILP) or a mixed-integer quadr…
A Unifying Complexity-Certification Framework for Branch-and-Bound Algorithms for Mixed-Integer Linear and Quadratic Programming
Shamisa Shoja, Daniel Arnström, Daniel Axehill
In model predictive control (MPC) for hybrid systems, solving optimization problems efficiently and with guarantees on worst-case computational complexity is critical to satisfy th…
A Dual Active-Set Solver for Embedded Quadratic Programming Using Recursive LDL' Updates
Daniel Arnström, Alberto Bemporad, Daniel Axehill
In this paper we present a dual active-set solver for quadratic programming which has properties suitable for use in embedded model predictive control applications. In particular,…
A Unifying Complexity Certification Framework for Active-Set Methods for Convex Quadratic Programming
Daniel Arnström, Daniel Axehill
In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these optimization problem…