SOTAVerified

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

Showing 12111220 of 1277 papers

TitleStatusHype
Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization0
A Weighted Common Subgraph Matching Algorithm0
Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives0
Real-time Crowd Tracking using Parameter Optimized Mixture of Motion Models0
Towards Decision Support Technology Platform for Modular Systems0
Cortical Processing with Thermodynamic-RAM0
Learning to Generate Coherent Summary with Discriminative Hidden Semi-Markov Model0
Quadratically constrained quadratic programming for classification using particle swarms and applications0
A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem0
Higher-Order Quantum-Inspired Genetic Algorithms0
Show:102550
← PrevPage 122 of 128Next →

No leaderboard results yet.