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Many high-dimensional optimisation problems exhibit rich geometric structures in their set of minimisers, often forming smooth manifolds due to over-parametrisation or symmetries. When this structure is known, at least locally, it can be…

Optimization and Control · Mathematics 2025-10-27 Evan Markou , Thalaiyasingam Ajanthan , Stephen Gould

This paper deals with the representation and solution of asymmetric Bayesian decision problems. We present a formal framework, termed asymmetric influence diagrams, that is based on the influence diagram and allows an efficient…

Artificial Intelligence · Computer Science 2013-01-18 Thomas D. Nielsen , Finn Verner Jensen

Mixed-Integer Quadratic Programming (MIQP) has been identified as a suitable approach for finding an optimal solution to the behavior planning problem with low runtimes. Logical constraints and continuous equations are optimized alongside.…

Robotics · Computer Science 2021-01-14 Klemens Esterle , Tobias Kessler , Alois Knoll

In this paper, we propose a trajectory optimization for computing smooth collision free trajectories for nonholonomic curvature bounded vehicles among static and dynamic obstacles. One of the key novelties of our formulation is a hierarchal…

In the field of nonlinear mechanics, many challenging problems (e.g. plasticity, contact, masonry structures, nonlinear membranes) turn out to be expressible as conic programs. In general, such problems are non-smooth in nature (plasticity…

Optimization and Control · Mathematics 2022-02-03 Jeremy Bleyer

In this paper we address several constrained transportation optimization problems (e.g. vehicle routing, shortest Hamiltonian path), for which we present novel algorithmic solutions and extensions, considering several optimization…

Data Structures and Algorithms · Computer Science 2009-03-24 Mugurel Ionut Andreica , Sorin Briciu , Madalina Ecaterina Andreica

Solving optimal control problems (OCPs) of autonomous agents operating under spatial and temporal constraints fast and accurately is essential in applications ranging from eco-driving of autonomous vehicles to quadrotor navigation. However,…

Robotics · Computer Science 2026-01-07 Shiying Dong , Zhipeng Shen , Rudolf Reiter , Hailong Huang , Bingzhao Gao , Hong Chen , Wen-Hua Chen

This paper investigates the use of multiple directions of stratification as a variance reduction technique for Monte Carlo simulations of path-dependent options driven by Gaussian vectors. The precision of the method depends on the choice…

Computational Finance · Quantitative Finance 2010-04-29 Benjamin Jourdain , Bernard Lapeyre , Piergiacomo Sabino

We study a class of combinatorial scheduling problems characterized by a particular type of constraint often associated with electrical power or gas energy. This constraint appears in several practical applications and is expressed as a sum…

Data Structures and Algorithms · Computer Science 2023-12-27 Trung Thanh Nguyen , Khaled Elbassioni , Areg Karapetyan , Majid Khonji

In this paper, we consider a number of results and seven conjectures on properly edge-coloured (PC) paths and cycles in edge-coloured multigraphs. We overview some known results and prove new ones. In particular, we consider a family of…

Discrete Mathematics · Computer Science 2008-05-31 Gregory Gutin , Eun Jung Kim

We address the problem of finding harmonic colors, this problem has many applications, from fashion to industrial design. In order to solve this problem we consider that colors follow normal distributions in tone (chroma and lightness) and…

Computer Vision and Pattern Recognition · Computer Science 2017-09-08 Carlos Lara-Alvarez , Tania Reyes

We present randomized algorithms for some well-studied, hard combinatorial problems: the k-path problem, the p-packing of q-sets problem, and the q-dimensional p-matching problem. Our algorithms solve these problems with high probability in…

Data Structures and Algorithms · Computer Science 2010-07-08 Andreas Björklund , Thore Husfeldt , Petteri Kaski , Mikko Koivisto

Our aim is to explain mathematical programs with equilibrium constraints (MPECs), motivate them through applications, present the main equivalent formulations of equilibrium constraints, and summarize the basic existence theory for optimal…

Optimization and Control · Mathematics 2026-05-04 Louis Shuo Wang

Graphs are ubiquitous data structures for representing interactions between entities. With an emphasis on the use of graphs to represent chemical molecules, we explore the task of learning to generate graphs that conform to a distribution…

Machine Learning · Computer Science 2019-03-08 Qi Liu , Miltiadis Allamanis , Marc Brockschmidt , Alexander L. Gaunt

We introduce and study conic geometric programs (CGPs), which are convex optimization problems that unify geometric programs (GPs) and conic optimization problems such as semidefinite programs (SDPs). A CGP consists of a linear objective…

Optimization and Control · Mathematics 2013-10-14 Venkat Chandrasekaran , Parikshit Shah

The orientation completion problem for a class of oriented graphs asks whether a given partially oriented graph can be completed to an oriented graph in the class by orienting the unoriented edges of the partially oriented graph.…

Combinatorics · Mathematics 2022-11-07 Kevin Hsu , Jing Huang

In this paper we present the use of Constraint Programming for solving balanced academic curriculum problems. We discuss the important role that heuristics play when solving a problem using a constraint-based approach. We also show how…

Programming Languages · Computer Science 2007-05-23 Carlos Castro , Sebastian Manzano

We describe an effective landscape introduced in [1] for the analysis of Constraint Satisfaction problems, such as Sphere Packing, K-SAT and Graph Coloring. This geometric construction reexpresses these problems in the more familiar terms…

Quantum Physics · Physics 2008-09-25 Florent Krzakala , Jorge Kurchan

The article proposes an n-dimensional mathematical model of the visual representation of a linear programming problem. This model makes it possible to use artificial neural networks to solve multidimensional linear optimization problems,…

Optimization and Control · Mathematics 2022-08-18 Nikolay A. Olkhovsky , Leonid B. Sokolinsky

This paper considers decentralized optimization of convex functions with mixed affine equality constraints involving both local and global variables. Constraints on global variables may vary across different nodes in the network, while…

Optimization and Control · Mathematics 2026-02-05 Demyan Yarmoshik , Nhat Trung Nguyen , Alexander Rogozin , Alexander Gasnikov
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