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20142026
most citedOptimization Problems for Machine Learning: A Survey

373 citations · 852 across the 17 of their papers we have counts for

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13 papers · 1 filter

math.OC2025

Solving Sparse Mixed-Integer Quadratic Problems: Application to the Unit Commitment Problem with Optimal Power Flow

Ignacio Gómez-Casares, Pietro Belotti, Bissan Ghaddar +1

Mixed-Integer Quadratically Constrained Quadratic Programs (MIQCQP) arise in a variety of applications, particularly in energy, water, and gas systems, where discrete decisions int…

math.OC2024

Learning in Spatial Branching: Limitations of Strong Branching Imitation

Brais González-Rodríguez, Ignacio Gómez-Casares, Bissan Ghaddar +2

Over the last few years, there has been a surge in the use of learning techniques to improve the performance of optimization algorithms. In particular, the learning of branching ru…

math.OC2024

Three Network Design Problems for Community Energy Storage

Bissan Ghaddar, Ivana Ljubic, Yuying Qiu

In this paper, we develop novel mathematical models to optimize utilization of community energy storage (CES) by clustering prosumers and consumers into energy sharing communities/…

math.OC2024★ 4 cited

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process

Zhenan Fan, Bissan Ghaddar, Xinglu Wang +3

The rapid advancement of artificial intelligence (AI) techniques has opened up new opportunities to revolutionize various fields, including operations research (OR). This survey pa…

math.OC2022★ 1 cited

Polynomial Optimization: Enhancing RLT relaxations with Conic Constraints

Brais González-Rodríguez, Raúl Alvite-Pazó, Samuel Alvite-Pazó +2

Conic optimization has recently emerged as a powerful tool for designing tractable and guaranteed algorithms for non-convex polynomial optimization problems. On the one hand, tract…

math.OC2022★ 1 cited

Adaptive robust electric vehicle routing under energy consumption uncertainty

Jaehee Jeong, Bissan Ghaddar, Nicolas Zufferey +1

Electric vehicles (EVs) have been highly favoured as a future transportation mode in the transportation section in recent years. EVs have many advantages compared to traditional tr…

math.OC2022★ 1 cited

Learning for Spatial Branching: An Algorithm Selection Approach

Bissan Ghaddar, Ignacio Gómez-Casares, Julio González-Díaz +3

The use of machine learning techniques to improve the performance of branch-and-bound optimization algorithms is a very active area in the context of mixed integer linear problems,…

math.OC2021

Two-Stage Robust Quadratic Optimization with Equalities and its Application to Optimal Power Flow

Olga Kuryatnikova, Bissan Ghaddar, Daniel K. Molzahn

In this work, we consider two-stage quadratic optimization problems under ellipsoidal uncertainty. In the first stage, one needs to decide upon the values of a subset of optimizati…

math.OC2020★ 120 cited

Electric Vehicle Routing and Charging/Discharging under Time-Variant Electricity Prices

Bo Lin, Bissan Ghaddar, Jatin Nathwani

The integration of electric vehicles (EVs) with the energy grid has become an important area of research due to the increasing EV penetration in today's transportation systems. Und…

math.OC2019★ 373 cited

Optimization Problems for Machine Learning: A Survey

Claudio Gambella, Bissan Ghaddar, Joe Naoum-Sawaya

This paper surveys the machine learning literature and presents in an optimization framework several commonly used machine learning approaches. Particularly, mathematical optimizat…

math.OC2017★ 4 cited

AC Transmission Network Expansion Planning: A Semidefinite Programming Branch-and-Cut Approach

Bissan Ghaddar, Rabih Jabr

Transmission network expansion planning is a mixed-integer optimization problem, whose solution is used to guide future investment in transmission equipment. An approach is present…

math.OC2015★ 7 cited

Alternative SDP and SOCP Approximations for Polynomial Optimization

Xiaolong Kuang, Bissan Ghaddar, Joe Naoum-Sawaya +1

In theory, hierarchies of semidefinite programming (SDP) relaxations based on sum of squares (SOS) polynomials have been shown to provide arbitrarily close approximations for a gen…

math.OC2014★ 132 cited

Optimal Power Flow as a Polynomial Optimization Problem

Bissan Ghaddar, Jakub Marecek, Martin Mevissen

Formulating the alternating current optimal power flow (ACOPF) as a polynomial optimization problem makes it possible to solve large instances in practice and to guarantee asymptot…