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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 426–450 of 1277 papers

TitleStatusHype
A General Large Neighborhood Search Framework for Solving Integer Linear Programs—0
A Comparison of Greedy and Optimal Assessment of Natural Language Student Input Using Word-to-Word Similarity Metrics—0
CoCo: Learning Strategies for Online Mixed-Integer Control—0
A Novel Column Generation Heuristic for Airline Crew Pairing Optimization with Large-scale Complex Flight Networks—0
The Curious Case of Class Accuracy Imbalance in LLMs: Post-hoc Debiasing via Nonlinear Integer Programming—0
A novel channel pruning method for deep neural network compression—0
Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology—0
Clustering Binary Data by Application of Combinatorial Optimization Heuristics—0
An Optimal Quadratic Approach to Monolingual Paraphrase Alignment—0
Exact and Approximate Hierarchical Clustering Using A*—0
Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization—0
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions—0
Annealing Machine-assisted Learning of Graph Neural Network for Combinatorial Optimization—0
A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms—0
A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem—0
A 10.8mW Mixed-Signal Simulated Bifurcation Ising Solver using SRAM Compute-In-Memory with 0.6us Time-to-Solution—0
Evolutionary RL for Container Loading—0
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits—0
Chemical Reaction Optimization for the Set Covering Problem—0
Evolutionary Construction of Perfectly Balanced Boolean Functions—0
Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives—0
Cheaper and Better: Selecting Good Workers for Crowdsourcing—0
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms—0
Annealed Training for Combinatorial Optimization on Graphs—0
Evolutionary Approach for the Containers Bin-Packing Problem—0
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