An approximation Lagrangian-based algorithm for the maximum clique problem via deterministic annealing neural network

DOI10.1016/j.jfranklin.2022.06.009OpenAlexW4282823693WikidataQ114160022 ScholiaQ114160022MaRDI QIDQ2159961

Jinyu Dai, Baoping Jiang, Zhengtian Wu, Hamid Reza Karimi, Guangquan Lu

Publication date: 2 August 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2022.06.009

Mathematics Subject Classification ID

Systems theory; control (93-XX) Information and communication theory, circuits (94-XX)

Related Items (1)

Dynamic path planning of mobile robot based on improved simulated annealing algorithm

Uses Software

• QUALEX
• NuMVC

Cites Work

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• A deterministic annealing algorithm for approximating a solution of the min-bisection problem
• Breakout local search for maximum clique problems
• An adaptive multistart tabu search approach to solve the maximum clique problem
• An exact bit-parallel algorithm for the maximum clique problem
• An efficient branch-and-bound algorithm for finding a maximum clique with computational experiments
• An exact algorithm for the maximum clique problem
• Random constraint satisfaction: easy generation of hard (satisfiable) instances
• STABULUS: A technique for finding stable sets in large graphs with tabu search
• The maximum clique problem
• Performance of neural net heuristics for maximum clique on diverse highly compressible graphs
• On minimization of the number of branches in branch-and-bound algorithms for the maximum clique problem
• Multi-threading a state-of-the-art maximum clique algorithm
• Multi-neighborhood tabu search for the maximum weight clique problem
• WSVR-based fuzzy neural network with annealing robust algorithm for system identification
• An improved bit parallel exact maximum clique algorithm
• An opposition-based memetic algorithm for the maximum quasi-clique problem
• An approximation algorithm for graph partitioning via deterministic annealing neural network
• Towards faster local search for minimum weight vertex cover on massive graphs
• Phased local search for the maximum clique problem
• A new trust region technique for the maximum weight clique problem
• A simple simulated annealing algorithm for the maximum clique problem
• An error-correcting code framework for genetic sequence analysis
• A review on algorithms for maximum clique problems
• Parallel Maximum Clique Algorithms with Applications to Network Analysis
• A global optimization approach for solving the maximum clique problem
• NuMVC: An Efficient Local Search Algorithm for Minimum Vertex Cover
• Incremental Upper Bound for the Maximum Clique Problem
• A branch and bound algorithm for the maximum clique problem
• A branch and bound algorithm for the maximum clique problem

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