no code implementations • 9 Apr 2024 • Manav Mishra, Hritik Bana, Saswata Sarkar, Sujeevraja Sanjeevi, PB Sujit, Kaarthik Sundar
This article presents a deep reinforcement learning-based approach to tackle a persistent surveillance mission requiring a single unmanned aerial vehicle initially stationed at a depot with fuel or time-of-flight constraints to repeatedly visit a set of targets with equal priority.
no code implementations • 14 Mar 2023 • Yuqi Zhou, Kaarthik Sundar, Deepjyoti Deka, Hao Zhu
Wildfires pose a significant threat to the safe and reliable operation of electric power systems.
1 code implementation • 31 Mar 2022 • Shriram Srinivasan, Kaarthik Sundar, Vitaliy Gyrya, Anatoly Zlotnik
We identify criteria based on the uniqueness of solutions under which the existence of a non-physical generalized solution found by a non-linear solver implies non-existence of a physical solution, i. e., infeasibility of the problem.
no code implementations • 3 Mar 2021 • Sai Krishna Kanth Hari, Kaarthik Sundar, Shriram Srinivasan, Anatoly Zlotnik, Russell Bent
In particular, a reservoir is modeled as a rigid, hollow container that stores gas under isothermal conditions and uniform density, and a well is modeled as a vertical pipe.
Optimization and Control
no code implementations • 21 Dec 2020 • Elena Khlebnikova, Kaarthik Sundar, Anatoly Zlotnik, Russell Bent, Mary Ewers, Byron Tasseff
The majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines.
Optimization and Control 76B75, 90C35
1 code implementation • 27 May 2020 • Kaarthik Sundar, Sujeevraja Sanjeevi, Harsha Nagarajan
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
2 code implementations • 9 Dec 2019 • Kaarthik Sundar, Sujeevraja Sanjeevi
This paper formulates a team orienteering problem with multiple fixed-wing drones and develops a branch-and-price algorithm to solve the problem to optimality.
Optimization and Control
2 code implementations • 6 Nov 2017 • Carleton Coffrin, Russell Bent, Kaarthik Sundar, Yeesian Ng, Miles Lubin
This work provides a brief introduction to the design of PowerModels, validates its implementation, and demonstrates its effectiveness with a proof-of-concept study analyzing five different formulations of the Optimal Power Flow problem.
Optimization and Control Computational Engineering, Finance, and Science
2 code implementations • 9 Jul 2017 • Harsha Nagarajan, Mowen Lu, Site Wang, Russell Bent, Kaarthik Sundar
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
2 code implementations • 18 Apr 2017 • Kaarthik Sundar, Carleton Coffrin, Harsha Nagarajan, Russell Bent
A general cutting-plane algorithm is proposed to solve the convex relaxation and linear approximations of the $N$-$k$ problem.
Systems and Control
1 code implementation • 15 Mar 2017 • Kaarthik Sundar, Harsha Nagarajan, Line Roald, Sidhant Misra, Russell Bent, Daniel Bienstock
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