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 12211230 of 1277 papers

TitleStatusHype
Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search0
Fixed Priority Global Scheduling from a Deep Learning Perspective0
Focused Jump-and-Repair Constraint Handling for Fixed-Parameter Tractable Graph Problems Closed Under Induced Subgraphs0
Forecasting high-dimensional dynamics exploiting suboptimal embeddings0
Fragmentation trees reloaded0
From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms0
Fuzzy Integer Linear Programming Mathematical Models for Examination Timetable Problem0
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization0
GenCO: Generating Diverse Designs with Combinatorial Constraints0
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization0
Show:102550
← PrevPage 123 of 128Next →

No leaderboard results yet.