Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
A review on particle swarm optimization algorithms and their applications to data clustering
Artificial Intelligence Review
A modified harmony search threshold accepting hybrid optimization algorithm
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
MGPSO --- the managed evolutionary optimization
SIDE'12 Proceedings of the 2012 international conference on Swarm and Evolutionary Computation
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
An improved adaptive binary Harmony Search algorithm
Information Sciences: an International Journal
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
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Particle swarm optimization (PSO) has gained increasing attention in tackling optimization problems. Its further superiority when hybridized with other techniques is also shown. In this paper a novel hybrid particle swarm optimization (NHPSO) is proposed in order to solve high dimensional optimization problems more efficiently, accurately and reliably. It provides a new architecture of hybrid algorithms, which organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to improve the search performance and this makes NHPSO algorithm have more powerful exploitation capabilities. Simulation and comparisons based on several well-studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed NHPSO.