Hybridization strategies for continuous ant colony optimization and particle swarm optimization applied to data clustering

A Multi-Objective Hybrid Aco-Pso Optimization Algorithm for Virtual Machine Placement in Cloud Computing

“…The proposed algorithm is simulated in cloudsim.The performance of the proposed hybrid ACO-PSO optimization algorithm is compared to multi-objective ant colony system (ACS) algorithm Yongqiang et al [7]. Chart 1 compares the total power consumed in each server when proposed hybrid ACO-PSO (HACOPSO) algorithm and Virtual Machine Placement Ant Colony System (VMPACS) algorithm are used.…”

“…In proposed hybrid ACO-PSO algorithm, hybridization is done sequentially [7] i.e., the VM placement solutions obtained by ACO algorithm are given as input to PSO algorithm. ACO algorithm finds VM placement solutions by considering resource wastage and power consumption in each server and PSO algorithm finds VM placement solution when considering fault tolerance through load balancing in each server.…”

Size optimization for hybrid photovoltaic–wind energy system using ant colony optimization for continuous domains based integer programming

“…Also, the authors introduced a novel procedure to generate artificial and mixed-variable benchmark function. Huang et al incorporated continuous ant colony optimization (ACO R ) with particle swarm optimization (PSO) to improve the search ability, investigating four types of hybridization including sequence approach, parallel approach, sequence approach with an enlarged pheromone-particle table and global best exchange [15]. These hybrid systems employed to data clustering.…”

A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm

“…Thus, the combination of different swarm algorithms, which regards as an efficient strategy, has been proposed to maintain the advantages of the original algorithms and achieve a superior solution quality. Generally, the performance of a single algorithm is inferior to that of the hybrid algorithm [45,46]. Hybridization of swarm algorithms has become a proposing alternative for performance enhancement of an original swarm intelligence optimization algorithm and has been applied to wide range of optimization problems.…”