Interior point method
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IPO: Interior-Point Policy Optimization under Constraints Open
In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints. We propose a novel first-order policy …
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Notes on Numerical Methods for Solving Optimal Control Problems Open
Recent advances in theory, algorithms, and computational power make it possible to solve complex, optimal control problems both for off-line and on-line industrial applications. This paper starts by reviewing the technical details of the s…
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Dual Quaternion-Based Powered Descent Guidance with State-Triggered Constraints Open
This paper presents a numerical algorithm for computing 6-degree-of-freedom\nfree-final-time powered descent guidance trajectories. The trajectory\ngeneration problem is formulated using a unit dual quaternion representation of\nthe rigid …
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A Quantum Interior Point Method for LPs and SDPs Open
We present a quantum interior point method (IPM) for semi-definite programs that has a worst-case running time of Õ( n 2.5 / ξ 2 μ κ 3 log(1/ϵ)). The algorithm outputs a pair of matrices ( S,Y ) that have objective value within ϵ of the op…
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A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources Open
Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). Here, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs…
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Characterizing the Reserve Provision Capability Area of Active Distribution Networks: A Linear Robust Optimization Method Open
Distributed energy resources (DERs) installed in active distribution networks (ADNs) can be exploited to provide both active and reactive power reserves to the upper-layer grid (i.e., sub-transmission and transmission systems) at their con…
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An Exact Sequential Linear Programming Algorithm for the Optimal Power Flow Problem Open
Despite major advancements in nonlinear programming (NLP) and convex relaxations, most system operators around the world still predominantly use some form of linear programming (LP) approximation of the AC power flow equations. This is lar…
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Exact Optimal Power Dispatch in Unbalanced Distribution Systems With High PV Penetration Open
Smart inverters provide additional control capability to help optimize the operation of distribution systems. This paper proposes a framework for exact optimal active and reactive power dispatch of distributed photovoltaic (PV) generation,…
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A primal-dual interior-point algorithm for nonsymmetric exponential-cone optimization Open
A new primal-dual interior-point algorithm applicable to nonsymmetric conic optimization is proposed. It is a generalization of the famous algorithm suggested by Nesterov and Todd for the symmetric conic case, and uses primal-dual scalings…
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Log-Barrier Interior Point Methods Are Not Strongly Polynomial Open
We prove that primal-dual log-barrier interior point methods are not strongly\npolynomial, by constructing a family of linear programs with $3r+1$\ninequalities in dimension $2r$ for which the number of iterations performed is\nin $\\Omega…
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Large-Scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications Open
In computer vision, many problems can be formulated as binary quadratic programs (BQPs), which are in general NP hard. Finding a solution when the problem is of large size to be of practical interest typically requires relaxation. Semidefi…
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Dispatching Stochastic Heterogeneous Resources Accounting for Grid and Battery Losses Open
We compute an optimal day-ahead dispatch plan for distribution networks with stochastic resources and batteries, while accounting for grid and battery losses. We formulate and solve a scenario-based AC Optimal Power Flow (OPF), which is by…
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Multi‐objective, multi‐year dynamic generation and transmission expansion planning‐ renewable energy sources integration for Iran's National Power Grid Open
The paper presents a multi-year, multi-objective framework for integrating Renewable Energy Sources (RESs) into the high voltage transmission network of Iran's National Power Grid (INPG). The objective functions in this study are the total…
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An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming Open
We consider a class of constrained optimization problems where the objective function is a sum of a smooth function and a nonconvex non-Lipschitz function. Many problems in sparse portfolio selection, edge preserving image restoration, and…
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Adversarially Robust Optimization with Gaussian Processes Open
In this paper, we consider the problem of Gaussian process (GP) optimization with an added robustness requirement: The returned point may be perturbed by an adversary, and we require the function value to remain as high as possible even af…
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A Primal-Dual Quasi-Newton Method for Exact Consensus Optimization Open
We introduce the primal-dual quasi-Newton (PD-QN) method as an approximated\nsecond order method for solving decentralized optimization problems. The PD-QN\nmethod performs quasi-Newton updates on both the primal and dual variables of\nthe…
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Arithmetic optimization algorithm based maximum power point tracking for grid-connected photovoltaic system Open
This paper suggests an optimal maximum power point tracking (MPPT) control scheme for a grid-connected photovoltaic (PV) system using the arithmetic optimization algorithm (AOA). The parameters of the proportional-integral (PI) controller-…
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Transient Stability-Constrained Optimal Power Flow Calculation With Extremely Unstable Conditions Using Energy Sensitivity Method Open
In this paper, a transient stability margin is proposed in terms of the kinetic energy of power systems in extremely unstable conditions. A unified energy-based transient stability constraint is formed for both normal and extremely unstabl…
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Power System State Estimation via Feasible Point Pursuit: Algorithms and Cramér-Rao Bound Open
Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bu…
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Robust Probabilistic-Constrained Optimization for IRS-Aided MISO Communication Systems Open
Taking into account imperfect channel state information, this letter formulates and solves a joint active/passive beamforming optimization problem in multiple-input single-output systems with the support of an intelligent reflecting surfac…
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Multiple-constraint cooperative guidance based on two-stage sequential convex programming Open
An improved approach is presented in this paper to implement highly constrained cooperative guidance to attack a stationary target. The problem with time-varying Proportional Navigation (PN) gain is first formulated as a nonlinear optimal …
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Constrained deep networks: Lagrangian optimization via Log-barrier extensions Open
This study investigates imposing hard inequality constraints on the outputs of convolutional neural networks (CNN) during training. Several recent works showed that the theoretical and practical advantages of Lagrangian optimization over s…
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Optimal Operation of a Combined Heat and Power System Considering Real-time Energy Prices Open
The combined heat and power (CHP) systems can provide heat and electricity simultaneously. They are promising in the future energy landscape because of high efficiency and low emissions. This paper proposes a new operation optimization mod…
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Interior Point Solving for LP-based prediction+optimisation Open
Solving optimization problems is the key to decision making in many real-life analytics applications. However, the coefficients of the optimization problems are often uncertain and dependent on external factors, such as future demand or en…
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On the complexity of an augmented Lagrangian method for nonconvex optimization Open
In this paper we study the worst-case complexity of an inexact augmented Lagrangian method for nonconvex constrained problems. Assuming that the penalty parameters are bounded we prove a complexity bound of $\mathcal{O}(|\log (\epsilon )|)…
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Arithmetic optimization algorithm based MPPT technique for centralized TEG systems under different temperature gradients Open
Since centralized thermoelectric power generation (TEG) system presents multiple local maximum power points (LMPPs) at different temperature gradients (DTG), thus its optimal power harvesting is difficult to realize via conventional approa…
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Adaptive solution of truss layout optimization problems with global stability constraints Open
Truss layout optimization problems with global stability constraints are nonlinear and nonconvex and hence very challenging to solve, particularly when problems become large. In this paper, a relaxation of the nonlinear problem is modelled…
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Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks Open
The power flow problem in three-phase unbalanced distribution networks is addressed in this research using a derivative-free numerical method based on the upper-triangular matrix. The upper-triangular matrix is obtained from the topologica…
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ADMM-Based Distributed Optimization of Hybrid MTDC-AC Grid for Determining Smooth Operation Point Open
Accompanied by the rising fashion of distributed energy resources requiring distributed optimization is becoming more prevalent among power system. However, research for distributed optimization to determine smooth operation point (SOP) ha…
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Layout optimization of simplified trusses using mixed integer linear programming with runtime generation of constraints Open
Traditional truss layout optimization employing the ground structure method will often generate layouts that are too complex to fabricate in practice. To address this, mixed integer linear programming can be used to enforce buildability co…