most citedA Convexification-based Outer-Approximation Method for Convex and Nonconvex MINLP

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

math.OC2025

Hybrid Quantum Branch-and-Bound Method for Quadratic Unconstrained Binary Optimization

Zedong Peng, Daniel de Roux, David E. Bernal Neira

Quantum algorithms have shown promise in solving Quadratic Unconstrained Binary Optimization (QUBO) problems, benefiting from their connection to the transverse field Ising model.…

math.OC2024

Addressing Discrete Dynamic Optimization via a Logic-Based Discrete-Steepest Descent Algorithm

Zedong Peng, Albert Lee, David E. Bernal Neira

Dynamic optimization problems involving discrete decisions have several applications, yet lead to challenging optimization problems that must be addressed efficiently. Combining di…

math.OC20242 cited

A Convexification-based Outer-Approximation Method for Convex and Nonconvex MINLP

Zedong Peng, Kaiyu Cao, Kevin C. Furman +3

The advancement of domain reduction techniques has significantly enhanced the performance of solvers in mathematical programming. This paper delves into the impact of integrating c…

math.OC2024

Measure This, Not That: Optimizing the Cost and Model-Based Information Content of Measurements

Jialu Wang, Zedong Peng, Ryan Hughes +3

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. This work extends popular MBDoE workflo…

quant-ph2024

Benchmarking Quantum Optimization for the Maximum-Cut Problem on a Superconducting Quantum Computer

Maxime Dupont, Bhuvanesh Sundar, Bram Evert +4

Achieving high-quality solutions faster than classical solvers on computationally hard problems is a challenge for quantum optimization to deliver utility. Using a superconducting…