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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

Showing 971980 of 1277 papers

TitleStatusHype
An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem0
Ant Colony Optimization and Hypergraph Covering Problems0
An Upper Bound for Minimum True Matches in Graph Isomorphism with Simulated Annealing0
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection0
A Polynomial Time Approximation Scheme for a Single Machine Scheduling Problem Using a Hybrid Evolutionary Algorithm0
Application of Decision Tree Classifier in Detection of Specific Denial of Service Attacks with Genetic Algorithm Based Feature Selection on NSL-KDD0
Application of QUBO solver using black-box optimization to structural design for resonance avoidance0
Application of the Brain Drain Optimization Algorithm to the N-Queens Problem0
Approximately Optimal Core Shapes for Tensor Decompositions0
Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference0
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