Optimization
Efficient solutions to large-scale problems.
Much of MERL's research activity involves formulating scientific and engineering problems as optimizations, which can be solved in an efficient way. We have developed fundamental algorithms to better solve classic problems, such as quadratic programs and minimum-cost paths. Our work also involves developing theoretical bounds to understand performance limits.
Quick Links
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Researchers
Stefano
Di Cairano
Arvind
Raghunathan
Toshiaki
Koike-Akino
Daniel N.
Nikovski
Christopher R.
Laughman
Yebin
Wang
Philip V.
Orlik
Ye
Wang
Abraham P.
Vinod
Kieran
Parsons
Avishai
Weiss
Scott A.
Bortoff
Diego
Romeres
Matthew
Brand
Petros T.
Boufounos
Hassan
Mansour
Jianlin
Guo
Pu
(Perry)
Wang
Vedang M.
Deshpande
Hongbo
Sun
Dehong
Liu
Hongtao
Qiao
Bingnan
Wang
Purnanand
Elango
Gordon
Wichern
Chungwei
Lin
Yanting
Ma
Saviz
Mowlavi
William S.
Yerazunis
Nobuyuki
Yoshikawa
Jinyun
Zhang
Abraham
Goldsmith
Shingo
Kobori
Pedro
Miraldo
Alexander
Schperberg
Anoop
Cherian
Radu
Corcodel
Jordan
Leung
Joshua
Rapp
Kenji
Inomata
Jing
Liu
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Awards
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AWARD Mitsubishi Electric and MERL work recognized with IEEJ Distinguished Paper Award Date: June 1, 2025
Awarded to: Arvind Raghunathan, Daniel Nikovski
MERL Contacts: Daniel N. Nikovski; Arvind Raghunathan
Research Areas: Electric Systems, OptimizationBrief- A publication jointly authored by Mitsubishi Electric Corporation's Advanced Technology Center (ATC) and MERL researchers has been recognized with the 2025 IEEJ Distinguished Paper Award by the Institute of Electrical Engineers Japan. The paper titled "Power Band Model Based on Flow Network and Weekly Unit Commitment Problem Considering Reserve Market" published in the IEEJ Transactions on Power and Energy presents a novel Unit Commitment formulation for scheduling the generator operations. Arvind Raghunathan and Daniel Nikovksi were co-authors on this publication.
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AWARD Mitsubishi Electric Team Wins Awards at GalFer Contest Date: June 23, 2025
Awarded to: Bingnan Wang, Tatsuya Yamamoto, Yusuke Sakamoto, Siyuan Sun, Toshiaki Koike-Akino, and Ye Wang
MERL Contacts: Toshiaki Koike-Akino; Bingnan Wang; Ye Wang
Research Areas: Machine Learning, Multi-Physical Modeling, OptimizationBrief- The MELSUR (Mitsubishi Electric SURrogate) team, consisting of a group of MERL and Mitsubishi Electric researchers, ranked first in two out of three categories in the GalFer Contest.
The GalFer (Galileo Ferraris) contest aims to compare the accuracy and efficiency of data-driven methodologies for the multi-physics simulation of traction electric machines. A total of 26 teams worldwide participated in the contest, which consists of three categories. The MELSUR team, including MERL staff Bingnan Wang, Toshiaki Koike-Akino, Ye Wang, MERL intern Siyuan Sun, Mitsubishi Electric researchers Tatsuya Yamamoto and Yusuke Sakamoto, ranked first for the category of "Novelty" and "Interpolation". The results were announced during an award ceremony at the COMPUMAG 2025 conference in Naples, Italy.
- The MELSUR (Mitsubishi Electric SURrogate) team, consisting of a group of MERL and Mitsubishi Electric researchers, ranked first in two out of three categories in the GalFer Contest.
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AWARD MERL Researchers Win Best Workshop Poster Award at the 2023 IEEE International Conference on Robotics and Automation (ICRA) Date: June 2, 2023
Awarded to: Yuki Shirai, Devesh Jha, Arvind Raghunathan and Dennis Hong
MERL Contact: Arvind Raghunathan
Research Areas: Artificial Intelligence, Optimization, RoboticsBrief- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
The paper presents a technique to manipulate an object using a tool in a closed-loop fashion using vision-based tactile sensors. More information about the workshop and the various speakers can be found here https://sites.google.com/view/icra2023embracingcontacts/home.
- MERL's paper titled: "Closed-Loop Tactile Controller for Tool Manipulation" Won the Best Poster Award in the workshop on "Embracing contacts : Making robots physically interact with our world". First author and MERL intern, Yuki Shirai, was presented with the award at a ceremony held at ICRA in London. MERL researchers Devesh Jha, Principal Research Scientist, and Arvind Raghunathan, Senior Principal Research Scientist and Senior Team Leader as well as Prof. Dennis Hong of University of California, Los Angeles are also coauthors.
See All Awards for Optimization -
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News & Events
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NEWS MERL researcher Purnanand Elango receives Best Paper Award at the AIAA SciTech Forum 2026. Date: January 12, 2026
Where: Orlando, FL
MERL Contact: Purnanand Elango
Research Areas: Control, OptimizationBrief- MERL research scientist Purnanand Elango received the Atmospheric Flight Mechanics (AFM) Best Paper Award at the AIAA SciTech Forum 2026 in January for the paper, “Auto-tuned Primal-dual Successive Convexification for Hypersonic Reentry Guidance.”, that he co-authored during his PhD research at the University of Washington, before joining MERL.
The paper presents a trajectory optimization method that reduces parameter-tuning effort for nonconvex optimization algorithms, such as sequential convex programming, in solving a challenging real-world optimal control problems.
The AIAA SciTech Forum is the flagship conference (more than 6000 attendees from 48 countries) of the American Institute of Aeronautics and Astronautics, the world's largest professional technical society dedicated to aerospace.
- MERL research scientist Purnanand Elango received the Atmospheric Flight Mechanics (AFM) Best Paper Award at the AIAA SciTech Forum 2026 in January for the paper, “Auto-tuned Primal-dual Successive Convexification for Hypersonic Reentry Guidance.”, that he co-authored during his PhD research at the University of Washington, before joining MERL.
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NEWS MERL researcher Abraham Vinod delivers an invited talk at CVXPY workshop 2026 Date: February 20, 2026
MERL Contact: Abraham P. Vinod
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researcher Abraham Vinod was an invited speaker at the inaugural CVXPY Workshop 2026, held at Stanford University, USA. CVXPY is an open-source, Python-embedded modeling language for convex optimization, and the workshop brought together researchers and practitioners to share ideas and real-world Python-based applications of convex optimization. Abraham’s talk, titled “pycvxset: Convex Sets in Python,” introduced MERL’s recently released open-source toolbox for convex set manipulation to the CVXPY community. The talk highlighted the toolbox’s capabilities and showcased recent applications in autonomous precision landing and robotics. The workshop details are available at https://www.cvxpy.org/workshop/2026/.
See All News & Events for Optimization -
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Research Highlights
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Internships
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CA0288: Internship - Spacecraft Guidance, Navigation, and Control
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CA0153: Internship - High-Fidelity Visualization and Simulation for Space Applications
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MS0254: Internship - Decentralized Data Assimilation for Large Scale Systems
See All Internships for Optimization -
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Openings
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MS0268: Research Scientist - Multiphysical Systems
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CI0177: Postdoctoral Research Fellow - Agentic AI
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OR0052: Research Scientist - Optimization Algorithms
See All Openings at MERL -
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Recent Publications
- , "Training Task Reasoning LLM Agents for Multi-turn Task Planning via Single-turn Reinforcement Learning", IEEE Control Systems Letters, DOI: 10.1109/LCSYS.2025.3642767, Vol. 9, pp. 2879-2884, February 2026.BibTeX TR2026-026 PDF
- @article{Hu2026feb,
- author = {Hu, Hanjiang and Liu, Changliu and Li, Na and Wang, Yebin},
- title = {{Training Task Reasoning LLM Agents for Multi-turn Task Planning via Single-turn Reinforcement Learning}},
- journal = {IEEE Control Systems Letters},
- year = 2026,
- volume = 9,
- pages = {2879--2884},
- month = feb,
- doi = {10.1109/LCSYS.2025.3642767},
- url = {https://www.merl.com/publications/TR2026-026}
- }
- , "Temporal Surrogate Lagrangian Decomposition for Operational Hosting Capacity Assessment In Unbalanced Power Distribution Systems", IEEE Transactions on Industrial Informatics, DOI: 10.1109/TII.2025.3650721, February 2026.BibTeX TR2026-025 PDF
- @article{Qin2026feb,
- author = {Qin, Jingtao and Sun, Hongbo and Yu, Nanpeng and Guo, Jianlin and Wang, Ye and Raghunathan, Arvind},
- title = {{Temporal Surrogate Lagrangian Decomposition for Operational Hosting Capacity Assessment In Unbalanced Power Distribution Systems}},
- journal = {IEEE Transactions on Industrial Informatics},
- year = 2026,
- month = feb,
- doi = {10.1109/TII.2025.3650721},
- url = {https://www.merl.com/publications/TR2026-025}
- }
- , "A Comparative Study of MINLP and MPVC Formulations for Solving Complex Nonlinear Decision-Making Problems in Aerospace Applications", Optimal Control Applications and Methods, February 2026.BibTeX TR2026-024 PDF
- @article{Ghezzi2026feb,
- author = {Ghezzi, Andrea and Nurkanović, Armin and Weiss, Avishai and Diehl, Moritz and {Di Cairano}, Stefano},
- title = {{A Comparative Study of MINLP and MPVC Formulations for Solving Complex Nonlinear Decision-Making Problems in Aerospace Applications}},
- journal = {Optimal Control Applications and Methods},
- year = 2026,
- month = feb,
- url = {https://www.merl.com/publications/TR2026-024}
- }
- , "Continuous-Time Successive Convexification for Passively-Safe Spacecraft Rendezvous on a Near Rectilinear Halo Orbit", AIAA SciTech Forum 2026, January 2026.BibTeX TR2026-016 PDF
- @inproceedings{Elango2026jan,
- author = {Elango, Purnanand and Vinod, Abraham P. and Kitamura, Kenji and Acikmese, Behcet and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Continuous-Time Successive Convexification for Passively-Safe Spacecraft Rendezvous on a Near Rectilinear Halo Orbit}},
- booktitle = {AIAA SciTech Forum 2026},
- year = 2026,
- month = jan,
- url = {https://www.merl.com/publications/TR2026-016}
- }
- , "Robust Optimal Control for Autonomous Precision Landing via Set-based Dynamic Programming", AIAA SciTech Forum, DOI: 10.2514/6.2026-0970, January 2026, pp. 2026-0970.BibTeX TR2026-015 PDF
- @inproceedings{Kamath2026jan,
- author = {Kamath, Abhinav and Vinod, Abraham P. and Elango, Purnanand and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Robust Optimal Control for Autonomous Precision Landing via Set-based Dynamic Programming}},
- booktitle = {AIAA SciTech 2026 Forum},
- year = 2026,
- pages = {2026--0970},
- month = jan,
- publisher = {AIAA},
- doi = {10.2514/6.2026-0970},
- url = {https://www.merl.com/publications/TR2026-015}
- }
- , "Relaxed barrier function based model predictive control with hard input constraints", IEEE Control Systems Letters, DOI: 10.1109/LCSYS.2025.3645287, Vol. 9, pp. 2927-2932, December 2025.BibTeX TR2026-005 PDF
- @article{Castroviejo-Fernandez2025dec,
- author = {Castroviejo-Fernandez, Miguel and Leung, Jordan},
- title = {{Relaxed barrier function based model predictive control with hard input constraints}},
- journal = {IEEE Control Systems Letters},
- year = 2025,
- volume = 9,
- pages = {2927--2932},
- month = dec,
- doi = {10.1109/LCSYS.2025.3645287},
- issn = {2475-1456},
- url = {https://www.merl.com/publications/TR2026-005}
- }
- , "Motion Planning for Information Acquisition via Continuous-time Successive Convexification", IEEE Conference on Decision and Control (CDC), December 2025.BibTeX TR2025-170 PDF
- @inproceedings{Uzun2025dec,
- author = {Uzun, Samet and Acikmese, Behcet and {Di Cairano}, Stefano},
- title = {{Motion Planning for Information Acquisition via Continuous-time Successive Convexification}},
- booktitle = {IEEE Control Systems Letters},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-170}
- }
- , "Set-based lossless convexification for a class of robust nonlinear optimal control problems", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC57313.2025.11312593, December 2025, pp. 1769-1776.BibTeX TR2025-160 PDF
- @inproceedings{Vinod2025dec,
- author = {Vinod, Abraham P. and Kamath, Abhinav and Weiss, Avishai and {Di Cairano}, Stefano},
- title = {{Set-based lossless convexification for a class of robust nonlinear optimal control problems}},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2025,
- pages = {1769--1776},
- month = dec,
- doi = {10.1109/CDC57313.2025.11312593},
- url = {https://www.merl.com/publications/TR2025-160}
- }
- , "Training Task Reasoning LLM Agents for Multi-turn Task Planning via Single-turn Reinforcement Learning", IEEE Control Systems Letters, DOI: 10.1109/LCSYS.2025.3642767, Vol. 9, pp. 2879-2884, February 2026.
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Videos
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Software & Data Downloads
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Convex sets in Python -
Meta-Learning State Space Models -
Python-based Robotic Control & Optimization Package -
Template Embeddings for Adiabatic Quantum Computation -
Quasi-Newton Trust Region Policy Optimization -
Convergent Inverse Scattering using Optimization and Regularization -
Optimal Recursive McCormick Linearization of MultiLinear Programs
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