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 451460 of 1277 papers

TitleStatusHype
Cheaper and Better: Selecting Good Workers for Crowdsourcing0
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks0
Annealed Training for Combinatorial Optimization on Graphs0
Exact Spin Elimination in Ising Hamiltonians and Energy-Based Machine Learning0
Evolutionary Approach for the Containers Bin-Packing Problem0
Experimental Analysis of Design Elements of Scalarizing Functions-based Multiobjective Evolutionary Algorithms0
Evaluation of bioinspired algorithms for the solution of the job scheduling problem0
Exploiting Problem Structure in Combinatorial Landscapes: A Case Study on Pure Mathematics Application0
Exploiting Promising Sub-Sequences of Jobs to solve the No-Wait Flowshop Scheduling Problem0
Chases and Escapes, and Optimization Problems0
Show:102550
← PrevPage 46 of 128Next →

No leaderboard results yet.