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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

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Showing 951–975 of 1277 papers

TitleStatusHype
MS-BACO: A new Model Selection algorithm using Binary Ant Colony Optimization for neural complexity and error reduction—0
Multi-Agent Deep Reinforcement Learning enabled Computation Resource Allocation in a Vehicular Cloud Network—0
Multidimensional Assignment Problem for multipartite entity resolution—0
Multi-IRS Enhanced Wireless Coverage: Deployment Optimization Based on Large-Scale Channel Knowledge—0
Multi-layer local optima networks for the analysis of advanced local search-based algorithms—0
Multi-objective Evolution of Heuristic Using Large Language Model—0
Multi-Passive/Active-IRS Enhanced Wireless Coverage: Deployment Optimization and Cost-Performance Trade-off—0
Multiple-gain Estimation for Running Time of Evolutionary Combinatorial Optimization—0
Sparse Multi-Reference Alignment : Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem—0
Multitasking Evolutionary Algorithm Based on Adaptive Seed Transfer for Combinatorial Problem—0
Near-Optimal LOS and Orientation Aware Intelligent Reflecting Surface Placement—0
Energy-Sensitive Trajectory Design and Restoration Areas Allocation for UAV-Enabled Grassland Restoration—0
Learning to Select and Rank from Choice-Based Feedback: A Simple Nested Approach—0
Network Interdiction Goes Neural—0
Neural Bee Colony Optimization: A Case Study in Public Transit Network Design—0
Neural Combinatorial Optimization: a New Player in the Field—0
Neural combinatorial optimization beyond the TSP: Existing architectures under-represent graph structure—0
Neural Combinatorial Optimization via Preference Optimization—0
Neural Combinatorial Optimization with Reinforcement Learning : Solving theVehicle Routing Problem with Time Windows—0
Neural Extensions: Training Neural Networks with Set Functions—0
Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching—0
Neural Large Neighborhood Search—0
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach—0
Neural Networks and (Virtual) Extended Formulations—0
Neural Networks for Local Search and Crossover in Vehicle Routing: A Possible Overkill?—0
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