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Navigating rigid body objects through crowded environments can be challenging, especially when narrow passages are presented. Existing sampling-based planners and optimization-based methods like mixed integer linear programming (MILP)…

Robotics · Computer Science 2024-09-19 Mingxin Yu , Chuchu Fan

Modern Mixed Integer Linear Programming (MILP) solvers use the Branch-and-Bound algorithm together with a plethora of auxiliary components that speed up the search. In recent years, there has been an explosive development in the use of…

Optimization and Control · Mathematics 2024-11-28 Lara Scavuzzo , Karen Aardal , Neil Yorke-Smith

Lagrangian relaxation stands among the most efficient approaches for solving a Mixed Integer Linear Programs (MILP) with difficult constraints. Given any duals for these constraints, called Lagrangian Multipliers (LMs), it returns a bound…

Machine Learning · Computer Science 2024-10-21 Francesco Demelas , Joseph Le Roux , Mathieu Lacroix , Axel Parmentier

Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an…

Systems and Control · Electrical Eng. & Systems 2025-06-19 Cédric Join , Jakub Orłowski , Antoine Chaillet , Madeleine Lowery , Hugues Mounier , Michel Fliess

Mixed Integer programs (MIPs) are typically solved by the Branch-and-Bound algorithm. Recently, Learning to imitate fast approximations of the expert strong branching heuristic has gained attention due to its success in reducing the running…

Optimization and Control · Mathematics 2023-07-03 Sahil Manchanda , Sayan Ranu

In this paper we present an efficient model of the neuronal potentials recorded by a deep brain stimulation microelectrode (DBS MER) in the subthalamic nucleus. It is shown that a computationally efficient filtered point process consisting…

Neurons and Cognition · Quantitative Biology 2016-07-05 Kristian J. Weegink , Paul A. Bellette , John J. Varghese , Peter A. Silburn , Paul A. Meehan , Andrew P. Bradley

Besides training, mathematical optimization is also used in deep learning to model and solve formulations over trained neural networks for purposes such as verification, compression, and optimization with learned constraints. However,…

Optimization and Control · Mathematics 2024-01-30 Jiatai Tong , Junyang Cai , Thiago Serra

Deep neural networks (DNNs) are widely studied in various applications. A DNN consists of layers of neurons that compute affine combinations, apply nonlinear operations, and produce corresponding activations. The rectified linear unit…

Machine Learning · Computer Science 2024-02-13 Navid Aftabi , Nima Moradi , Fatemeh Mahroo

Mixed Integer Programming (MIP) solvers rely on an array of sophisticated heuristics developed with decades of research to solve large-scale MIP instances encountered in practice. Machine learning offers to automatically construct better…

We present strong mixed-integer programming (MIP) formulations for high-dimensional piecewise linear functions that correspond to trained neural networks. These formulations can be used for a number of important tasks, such as verifying…

Optimization and Control · Mathematics 2020-01-23 Ross Anderson , Joey Huchette , Will Ma , Christian Tjandraatmadja , Juan Pablo Vielma

We present a Mixed Integer Linear Program (MILP) approach in order to model the nonlinear problem of minimizing the tire noise. We first take more industrial constraints into account than in a former work of the authors. Then, we associate…

Data Structures and Algorithms · Computer Science 2018-09-14 Matthias Becker , Nicolas Ginoux , Sebastien Martin , Zsuzsanna Roka

Artificial Neural Networks (ANNs) are prevalent machine learning models that are applied across various real-world classification tasks. However, training ANNs is time-consuming and the resulting models take a lot of memory to deploy. In…

Machine Learning · Computer Science 2022-06-27 Vrishabh Patil , Yonatan Mintz

Mixed-integer linear programming (MILP) plays a crucial role in artificial intelligence, biochemistry, finance, cryptography, etc. Notwithstanding popular for decades, the researches of MILP solvers are still limited by the resource…

Quantum Physics · Physics 2022-04-12 Hao Wang , Yu Pan , Wei Cui

Mixed-integer linear programming (MILP) is a powerful tool for addressing a wide range of real-world problems, but it lacks a clear structure for comparing instances. A reliable similarity metric could establish meaningful relationships…

Machine Learning · Computer Science 2025-07-16 Gwen Maudet , Grégoire Danoy

Mixed-integer linear programming (MILP) is at the core of many advanced algorithms for solving fundamental problems in combinatorial optimization. The complexity of solving MILPs directly correlates with their support size, which is the…

Data Structures and Algorithms · Computer Science 2023-05-16 Sebastian Berndt , Hauke Brinkop , Klaus Jansen , Matthias Mnich , Tobias Stamm

Deep Brain Stimulation (DBS) is an established and powerful treatment method in various neurological disorders. It involves chronically delivering electrical pulses to a certain stimulation target in the brain in order to alleviate the…

Systems and Control · Electrical Eng. & Systems 2023-10-03 Anna Franziska Frigge , Alexander Medvedev , Elena Jiltsova , Dag Nyholm

Uncertainty in surgery durations continues to be difficult to account for in operating room scheduling. In particular, it remains complex to accurately incorporate uncertainty in surgical overtime constraints within mixed-integer linear…

Optimization and Control · Mathematics 2026-04-29 Cindy Pistorius , J. Theresia van Essen

Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinson's disease (PD). Aside from factors such as instrumentation, treatment plans, and surgical protocols, the success of the…

Image and Video Processing · Electrical Eng. & Systems 2024-10-30 Yiming Xiao , Jonathan C. Lau , Dimuthu Hemachandra , Greydon Gilmore , Ali R. Khan , Terry M. Peters

Enhancing existing transmission lines is a useful tool to combat transmission congestion and guarantee transmission security with increasing demand and boosting the renewable energy source. This study concerns the selection of lines whose…

Optimization and Control · Mathematics 2022-07-20 Jian Liu , Rui Bo , Siyuan Wang

We solve large-scale mixed-integer linear programs (MILPs) via distributed asynchronous saddle point computation. This is motivated by the MILPs being able to model problems in multi-agent autonomy, e.g., task assignment problems and…

Optimization and Control · Mathematics 2022-11-23 Luke Fina , Matthew Hale