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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

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Showing 476–500 of 1277 papers

TitleStatusHype
Faster width-dependent algorithm for mixed packing and covering LPs—0
Evaluation of bioinspired algorithms for the solution of the job scheduling problem—0
Fast Hyperparameter Tuning for Ising Machines—0
Chases and Escapes, and Optimization Problems—0
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization—0
CHARME: A chain-based reinforcement learning approach for the minor embedding problem—0
Annealed Mean Field Descent Is Highly Effective for Quadratic Unconstrained Binary Optimization—0
A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design—0
Estudo comparativo de meta-heurísticas para problemas de colorações de grafos—0
Estimation of the yield curve for Costa Rica using combinatorial optimization metaheuristics applied to nonlinear regression—0
Fewer Truncations Improve Language Modeling—0
Charged particle tracking with quantum annealing-inspired optimization—0
Finding Support Examples for In-Context Learning—0
Assessing Distribution Network Flexibility via Reliability-based P-Q Area Segmentation—0
First-Order Bayesian Regret Analysis of Thompson Sampling—0
An Iterative Path-Breaking Approach with Mutation and Restart Strategies for the MAX-SAT Problem—0
ERL-MPP: Evolutionary Reinforcement Learning with Multi-head Puzzle Perception for Solving Large-scale Jigsaw Puzzles of Eroded Gaps—0
Characterization of Locality in Spin States and Forced Moves for Optimizations—0
Fixed Priority Global Scheduling from a Deep Learning Perspective—0
Chaos inspired Particle Swarm Optimization with Levy Flight for Genome Sequence Assembly—0
An Introduction to Quantum Machine Learning for Engineers—0
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles—0
Equivariant neural networks for recovery of Hadamard matrices—0
CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models—0
Entity Summarization: State of the Art and Future Challenges—0
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