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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 12511260 of 1277 papers

TitleStatusHype
Iterated Tabu Search Algorithm for Packing Unequal Circles in a Circle0
Evolutionary Approach for the Containers Bin-Packing Problem0
Efficient 3D Endfiring TRUS Prostate Segmentation with Globally Optimized Rotational Symmetry0
Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization0
An efficient algorithm for learning with semi-bandit feedback0
A Discrete State Transition Algorithm for Generalized Traveling Salesman Problem0
Improvement/Extension of Modular Systems as Combinatorial Reengineering (Survey)0
An Improved ACS Algorithm for the Solutions of Larger TSP Problems0
Note on Combinatorial Engineering Frameworks for Hierarchical Modular Systems0
Detecting Overlapping Temporal Community Structure in Time-Evolving Networks0
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