The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights [PDF]
Neural Information Processing Systems, 2022 Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolation, ignoring that they often stem from related data distributions in ...
Maxime Gasse +40 more
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On Some Optimization Problems on Permutations
Кібернетика та комп'ютерні технології, 2022 Numerous studies consider combinatorial optimization problems and their solution methods, since a large number of practical problems are described by means of combinatorial optimization models.
Georgy Donets, Vasyl Biletskyi
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A linear time algorithm to compute vertices that belong to all, some and no minimum dominating sets in a tree and its consequences [PDF]
Opuscula MathematicaWe provide a linear time algorithm for determining the sets of vertices that belong to all, some and no minimum dominating sets of a tree, respectively, thus improving the quadratic time algorithm of Benecke and Mynhardt in 2008 [S.
Radosław Ziemann, Paweł Żyliński
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Recent Advances in Combinatorial Optimization [PDF]
The Scientific World Journal, 2015 Dehua Xu +4 more
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Reinforcement Learning for Combinatorial Optimization: A Survey [PDF]
Computers & Operations Research, 2020 Combinatorial optimization (CO) is the workhorse of numerous important applications in operations research, engineering, and other fields and, thus, has been attracting enormous attention from the research community recently. Some efficient approaches to
Nina Mazyavkina +3 more
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Dynamical System-Based Computational Models for Solving Combinatorial Optimization on Hypergraphs
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2023 The intrinsic energy minimization in dynamical systems offers a valuable tool for minimizing the objective functions of computationally challenging problems in combinatorial optimization. However, most prior works have focused on mapping such dynamics to
Mohammad Khairul Bashar +3 more
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An L_1 then L_0 approach to the cardinality constrained mean-variance and mean-CVaR portfolio optimization problems [PDF]
Mathematics and Modeling in FinanceCardinality constrained portfolio optimization problems are widely used portfolio optimization models which incorporate restriction on the number of assets in the portfolio.
Maziar Salahi, Tahereh Khodamoradi
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Multi-scenario Load Combinatorial Optimization Based on Improved Greedy Algorithm
Zhongguo dianli, 2020 With the gradual formation of sales side market competition pattern, the electricity companies can improve the safety level of power grid and the quality of power supply through load combinatorial optimization to improve the load rate and reduce the cost
Yan WANG +4 more
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Gels, 2016 Combinatorial method/high throughput strategies, which have long been used in the pharmaceutical industry, have recently been applied to hydrogel optimization for tissue engineering applications.
Laura A. Smith Callahan
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Mathematical modeling of finite topologies
Karpatsʹkì Matematičnì Publìkacìï, 2020 Integer programming is a tool for solving some combinatorial optimization problems. In this paper, we deal with combinatorial optimization problems on finite topologies.
S.E. Monabbati, H. Torabi
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