Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Pennsylvania State UniversityUS558 papers
- University of Maryland, College ParkUS521 papers
- Massachusetts Institute of TechnologyUS457 papers
- University of California, BerkeleyUS447 papers
- Centre National de la Recherche ScientifiqueFR442 papers
- Columbia UniversityUS374 papers
- Université Libre de BruxellesBE370 papers
- The University of AdelaideAU343 papers
- California Institute of TechnologyUS337 papers
- Goddard Space Flight CenterUS327 papers
- University of Wisconsin–MadisonUS321 papers
- University of DelawareUS313 papers
260 papers · 1 filter
Exact Solutions to a Class of Constrained Optimal Control Problems via Lossless Convexification for Digital Control
Vaibhav Upadhyay, Siddhartha Ganguly, Debasish Chatterjee
This article establishes a new numerically viable technique for solving a class of constrained, nonconvex, continuous-time optimal control problems (OCPs) for linear systems that c…
Sparse Robust Optimal Control in Continuous-Time: A Computationally Viable Approach
Siddhartha Ganguly, Ashwin Aravind, Souvik Das +2
This article presents a novel, numerically viable algorithm for solving sparse robust optimal control problems in continuous time. We consider a constrained linear noisy system gov…
Integrated Routing and Trajectory Design for Satellite Servicing
Euihyeon Choi, Koki Ho
This paper studies the integrated spacecraft routing and trajectory optimization problem for satellite servicing missions involving partial en-route propellant replenishment. Unlik…
Fundamental Limits for Sensor-Based Control via the Gibbs Variational Principle
Vincent Pacelli, Evangelos A. Theodorou
Fundamental limits on the performance of feedback controllers are essential for benchmarking algorithms, guiding sensor selection, and certifying task feasibility -- yet few genera…
Data-driven joint optimization of maintenance and spare parts provisioning: A distributionally robust approach
Heraldo Rozas, Weijun Xie, Nagi Gebraeel +1
This paper investigates the joint optimization of condition-based maintenance and spare provisioning, incorporating insights obtained from sensor data. Prognostic models estimate c…
Integrating Column Generation and Large Neighborhood Search for Bus Driver Scheduling with Complex Break Constraints
Lucas Kletzander, Tommaso Mannelli Mazzoli, Nysret Musliu +1
The Bus Driver Scheduling Problem (BDSP) is a combinatorial optimization problem with the goal to design shifts to cover prearranged bus tours. The objective takes into account the…
Orbital Depot Location Optimization for Satellite Constellation Servicing with Low-Thrust Transfers
Euihyeon Choi, Koki Ho
This paper addresses the critical problem of co-optimizing the optimal locations for orbital depots and the sequence of in-space servicing for a satellite constellation. While most…
Tropical Fréchet Means: a polyhedral approach to exact optimization
Kamillo Ferry, Bo Lin, Carlos Améndola +2
The Fréchet mean is a fundamental notion of central tendency defined as a minimizer of a sum of squared distances in a general metric space. In this paper, we study Fréchet means i…
Safety on the Fly: Constructing Robust Safety Filters via Policy Control Barrier Functions at Runtime
Luzia Knoedler, Oswin So, Ji Yin +5
Control Barrier Functions (CBFs) have proven to be an effective tool for performing safe control synthesis for nonlinear systems. However, guaranteeing safety in the presence of di…
Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty
Tinghan Ye, Sikai Cheng, Amira Hijazi +1
The paper studies a large-scale order fulfillment problem for a leading e-commerce company in the United States. The challenge involves selecting fulfillment centers and shipping c…
Cornell University Uses Integer Programming to Optimize Final Exam Scheduling
Tinghan Ye, Adam S. Jovine, Willem van Osselaer +2
This paper presents an integer programming-based optimization framework designed to effectively address the complex final exam scheduling challenges encountered at Cornell Universi…
Constructing Tight Quadratic Relaxations for Global Optimization: II. Underestimating Difference-of-Convex (D.C.) Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
Recent advances in the efficiency and robustness of algorithms solving convex quadratically constrained quadratic programming (QCQP) problems motivate developing techniques for cre…
Constructing Tight Quadratic Relaxations for Global Optimization: I. Outer-Approximating Twice-Differentiable Convex Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency a…
Randomized quasi-Monte Carlo methods for risk-averse stochastic optimization
Olena Melnikov, Johannes Milz
We establish epigraphical and uniform laws of large numbers for sample-based approximations of law invariant risk functionals. These sample-based approximation schemes include Mont…
Cislunar Space Situational Awareness Constellation Design and Planning with Facility Location Problem
Yuri Shimane, Kento Tomita, Koki Ho
Driven by the surmounting interest for dedicated infrastructure in cislunar space, this work considers the satellite constellation design for cislunar space situational awareness (…
Convergence rates for ensemble-based solutions to optimal control of uncertain dynamical systems
Olena Melnikov, Johannes Milz
We consider optimal control problems involving nonlinear ordinary differential equations with uncertain inputs. Using the sample average approximation, we obtain optimal control pr…
Generalizing Space Logistics Network Optimization with Integrated Machine Learning and Mathematical Programming
Koki Ho, Yuri Shimane, Masafumi Isaji
Recent growing complexity in space missions has led to an active research field of space logistics and mission design. This research field leverages the key ideas and methods used…
Optimizing Multiple-Control Toffoli Quantum Circuit Design with Constraint Programming
Jihye Jung, Kevin Dalmeijer, Pascal Van Hentenryck
As quantum technology advances, the efficient design of quantum circuits has become an important area of research. This paper provides an introduction to the MCT quantum circuit de…
Equitably allocating wildfire resilience investments for power grids: The curse of aggregation and vulnerability indices
Madeleine Pollack, Ryan Piansky, Swati Gupta +1
Social vulnerability indices have increased traction for guiding infrastructure investment decisions to prioritize communities that need these investments most. One such plan is th…
Criticality measure-based error estimates for infinite dimensional optimization
Danlin Li, Johannes Milz
Motivated by optimization with differential equations, we consider optimization problems with Hilbert spaces as decision spaces. As a consequence of their infinite dimensionality,…
Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization
Lam M. Nguyen, Katya Scheinberg, Trang H. Tran
We develop and analyze stochastic variants of ISTA and a full backtracking FISTA algorithms [Beck and Teboulle, 2009, Scheinberg et al., 2014] for composite optimization without th…
Deterministic Multistage Constellation Reconfiguration Using Integer Programming and Sequential Decision-Making Methods
Hang Woon Lee, David O. Williams Rogers, Brycen D. Pearl +2
In this paper, we address the problem of reconfiguring Earth observation satellite constellation systems through multiple stages. The Multi-stage Constellation Reconfiguration Prob…
Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling
Jiawei Lu, Tinghan Ye, Wenbo Chen +1
Optimizing service schedules is pivotal to the reliable, efficient, and inclusive on-demand mobility. This pressing challenge is further exacerbated by the increasing needs of an a…
First order algorithms for computing linear and polyhedral estimates
Yannis Bekri, Anatoli Juditsky, Arkadi Nemirovski
It was recently shown [7, 9] that "properly built" linear and polyhedral estimates nearly attain minimax accuracy bounds in the problem of recovery of unknown signal from noisy obs…