Results 11 to 20 of about 4,882,239 (315)
Combinatorial optimization and reasoning with graph neural networks [PDF]
International Joint Conference on Artificial Intelligence, 2021 Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have mostly focused on solving problem instances in isolation, ignoring the fact that they often stem from related data ...
Quentin Cappart +5 more
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DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization [PDF]
Neural Information Processing Systems, 2023 Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO for a specific problem requires the expert design of knowledge-driven ...
Haoran Ye +4 more
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DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems [PDF]
Neural Information Processing Systems, 2022 Recently, deep reinforcement learning (DRL) models have shown promising results in solving NP-hard Combinatorial Optimization (CO) problems. However, most DRL solvers can only scale to a few hundreds of nodes for combinatorial optimization problems on ...
Ruizhong Qiu, Zhiqing Sun, Yiming Yang
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Combinatorial mesh optimization [PDF]
The Visual Computer, 2011 A new mesh optimization framework for 3D triangular surface meshes is presented, which formulates the task as an energy minimization problem in the same spirit as in Hoppe et al. (SIGGRAPH’93: Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques, 1993).
Vidal, Vincent +2 more
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Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization [PDF]
Neural Information Processing Systems, 2022 Deep reinforcement learning (DRL)-based combinatorial optimization (CO) methods (i.e., DRL-NCO) have shown significant merit over the conventional CO solvers as DRL-NCO is capable of learning CO solvers less relying on problem-specific expert domain ...
Minsu Kim, Junyoung Park, Jinkyoo Park
semanticscholar +1 more source
A Quantum-Inspired Tensor Network Algorithm for Constrained Combinatorial Optimization Problems
Frontiers in Physics, 2022 Combinatorial optimization is of general interest for both theoretical study and real-world applications. Fast-developing quantum algorithms provide a different perspective on solving combinatorial optimization problems.
Tianyi Hao +5 more
doaj +1 more source
Convex Combinatorial Optimization [PDF]
Discrete & Computational Geometry, 2004 We introduce the convex combinatorial optimization problem, a far reaching generalization of the standard linear combinatorial optimization problem. We show that it is strongly polynomial time solvable over any edge-guaranteed family, and discuss several applications.
Onn, Shmuel, Rothblum, Uriel G.
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Combinatorial optimization with physics-inspired graph neural networks [PDF]
Nature Machine Intelligence, 2021 Combinatorial optimization problems are pervasive across science and industry. Modern deep learning tools are poised to solve these problems at unprecedented scales, but a unifying framework that incorporates insights from statistical physics is still ...
M. Schuetz +2 more
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Direct Combinatorial Pathway Optimization [PDF]
ACS Synthetic Biology, 2016 Combinatorial engineering approaches are becoming increasingly popular, yet they are hindered by the lack of specialized techniques for both efficient introduction of sequence variability and assembly of numerous DNA parts, required for the construction of lengthy multigene pathways.
Pieter Coussement +3 more
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A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems
IEEE Access, 2021 This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz.
Shanu Verma, M. Pant, V. Snás̃el
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