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Found 8 papers, 6 papers with code
A Modified Benders Decomposition for Chance-Constrained Unit Commitment with N-1 Security and Wind Uncertainty
As renewable wind energy penetration rates continue to increase, one of the major challenges facing grid operators is the question of how to control transmission grids in a reliable and a cost-efficient manner.
Systems and Control
Probabilistic $N$-$k$ Failure-Identification for Power Systems
A general cutting-plane algorithm is proposed to solve the convex relaxation and linear approximations of the $N$-$k$ problem.
Systems and Control
Evaluating Ising Processing Units with Integer Programming
The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, present new opportunities for hybrid-optimization algorithms that are hardware accelerated by these devices.
An Adaptive, Multivariate Partitioning Algorithm for Global Optimization of Nonconvex Programs
In this work, we develop an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) with multi-linear terms to global optimality.
Optimization and Control Systems and Control
Juniper: An Open-Source Nonlinear Branch-and-Bound Solver in Julia
Nonconvex mixed-integer nonlinear programs (MINLPs) represent a challenging class of optimization problems that often arise in engineering and scientific applications.
Optimization and Control
Sequence of Polyhedral Relaxations for Nonlinear Univariate Functions
Given a nonlinear, univariate, bounded, and differentiable function $f(x)$, this article develops a sequence of Mixed Integer Linear Programming (MILP) and Linear Programming (LP) relaxations that converge to the graph of $f(x)$ and its convex hull, respectively.
Optimization and Control
Optimal Robust Network Design: Formulations and Algorithms for Maximizing Algebraic Connectivity
This paper focuses on designing edge-weighted networks, whose robustness is characterized by maximizing algebraic connectivity, or the second smallest eigenvalue of the Laplacian matrix.
Learning for Interval Prediction of Electricity Demand: A Cluster-based Bootstrapping Approach
Days with similar demand patterns are grouped in clusters using an unsupervised learning algorithm and these clusters are used to partition the memory.
