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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 261270 of 1277 papers

TitleStatusHype
AED: An Anytime Evolutionary DCOP Algorithm0
Cakewalk Sampling0
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention0
An Improved ACS Algorithm for the Solutions of Larger TSP Problems0
An Expandable Machine Learning-Optimization Framework to Sequential Decision-Making0
Budgeted Influence Maximization for Multiple Products0
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization0
A Class of Linear Programs Solvable by Coordinate-Wise Minimization0
Systematic and Efficient Construction of Quadratic Unconstrained Binary Optimization Forms for High-order and Dense Interactions0
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization0
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