An Ant Based Particle Swarm Optimization Algorithm for Maximum Clique Problem in Social Networks

2014 ◽  
pp. 295-304 ◽  
Author(s):  
Mohammad Soleimani-pouri ◽  
Alireza Rezvanian ◽  
Mohammad Reza Meybodi
Keyword(s):  
Social Networks ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Maximum Clique ◽  
Maximum Clique Problem ◽  
Swarm Optimization ◽  
Clique Problem

Solving the Maximum Clique Problem using a Hybrid Particle Swarm Optimization Algorithm

2018 ◽  
Vol 9 (4) ◽  
pp. 21-35 ◽  
Author(s):  
Dalila Tayachi ◽  
Marwa Khemiri
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Maximum Clique ◽  
Maximum Clique Problem ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization ◽  
Clique Problem

This article tackles the maximum clique problem MCP known as an NP-hard graph problem. The maximum clique problem consists in finding in an undirected graph a complete sub-graph (clique) of maximum cardinality. As the MCP is a classical graph problem extensively studied, the main contribution of this paper is to use for the first time particle swarm to solve it. A hybrid particle swarm optimization algorithm HPSOD is proposed. First a PSO algorithm is designed, based on a sub-graph extraction approach named circular-arc graph CAG, then a local search heuristic is integrated to enhance its performance. Experimental tests carried out on DIMACS benchmarks show a globally good performance of the proposed algorithm and that it outperforms many existent approaches.

scholarly journals A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm

2015 ◽  
Vol 15 (2) ◽  
pp. 23-35 ◽  
Author(s):  
Li Zhao Xing ◽  
He Li Le ◽  
Zhang Hui
Keyword(s):  
Social Networks ◽  
Particle Swarm Optimization ◽  
Social Network ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Structural Balance

AbstractExploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural balance of social networks as a mathematical optimization problem by using swarm intelligence, and an efficient discrete particle swarm optimization algorithm was proposed to solve the modeled optimization problem. To take advantage of the topologies of social networks in the algorithm design, the discrete representation of the particle was redefined, and the discrete particle update principles were redesigned. To validate the efficiency of the proposed algorithm, experiments were conducted using synthetic and real-world social networks. The experiments demonstrate that the proposed algorithm not only achieves a balanced social network structure, but also automatically detects the community topology of networks.

Multi-Scale Cooperative Mutation Particle Swarm Optimization Algorithm

2012 ◽  
Vol 23 (7) ◽  
pp. 1805-1815 ◽  
Author(s):  
Xin-Min TAO ◽  
Fu-Rong LIU ◽  
Yu LIU ◽  
Zhi-Jing TONG
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Scale
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