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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 176–200 of 1277 papers

TitleStatusHype
Automatic Truss Design with Reinforcement LearningCode1
MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling ProblemCode1
Matrix Encoding Networks for Neural Combinatorial OptimizationCode1
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with DroneCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionsCode1
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial OptimizationCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
Multi Agent Reinforcement Learning for Sequential Satellite Assignment ProblemsCode1
Hybrid Pointer Networks for Traveling Salesman Problems OptimizationCode1
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit SynthesisCode1
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling ProblemsCode1
Neural Combinatorial Optimization for Real-World RoutingCode1
Belief Propagation Neural NetworksCode1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint ProgrammingCode1
Application of Decision Tree Classifier in Detection of Specific Denial of Service Attacks with Genetic Algorithm Based Feature Selection on NSL-KDD—0
A Polynomial Time Approximation Scheme for a Single Machine Scheduling Problem Using a Hybrid Evolutionary Algorithm—0
Distributed Task Offloading and Resource Allocation for Latency Minimization in Mobile Edge Computing Networks—0
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection—0
An Upper Bound for Minimum True Matches in Graph Isomorphism with Simulated Annealing—0
A Genetic Algorithm for solving Quadratic Assignment Problem(QAP)—0
A Generative Neural Annealer for Black-Box Combinatorial Optimization—0
A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and Minimum Vertex Cover—0
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