The advantage of this algorithm is its faster convergence rate with effective exploration and exploitation capability. The algorithm also has a moderate number of process parameters and computational complexity. To evaluate the capability total 30 benchmark instances and 5 real-life problems are solved ...
In this context, an improvement of the Artificial Bee Colony (ABC) algorithm, called the Artificial super-Bee enhanced Colony (AsBeC), is presented. AsBeC is designed to provide fast convergence speed, high solution accuracy and robust performance over a wide range of problems. It implements ...
In this study, well-known evolutionary algorithms such as Evolution Strategy, Genetic Algorithm, Differential Evolution, Adaptive Differential Evolution and swarm-based algorithms such as Particle Swarm Optimization, Artificial Bee Colony, Cuckoo Search and Differential Search Algorithm have been used for ...
algorithm would compare to a queue-based swarm algorithm regarding the detection rate and detection speed. Research objective 4 is to investigate how swarm algorithms perform on a larger scale in a smart building with more IoT devices and, therefore, more agents in the swarm than with a smart ...
The efficacy of this algorithm is further compared with several well-regarded metaheuristic approaches based on the generated optimal solutions. In addition, we also executed the proposed algorithm on six constrained and one unconstrained engineering design problems to further verify its robustness. The ...
involving a swarm intelligence-based optimization algorithm along with the CNN framework for the HAR task. First, we extract four distinctive spatio-temporal feature vectors from the relative movements of the skeletal joints. These features are thereafter encoded into images, which are fed to the CNN...
The results show that the PSO with mutation algorithm is significantly better than other PSO-based algorithms because it can overcome the drawback of trapping in the local optimum points and obtain better inverse solutions. The effects of measurement errors, number of dimensionalities, and number ...
This paper proposes a novel multi-hybrid algorithm named DHPN, using the best-known properties of dwarf mongoose algorithm (DMA), honey badger algorithm (HBA), prairie dog optimizer (PDO), cuckoo search (CS), grey wolf optimizer (GWO) and naked mole rat
The performance of the proposed algorithm is compared with that of the differential evolutionary (DE), genetic algorithm (GA), PSO, BBO, blended BBO and hybrid BBO-DE algorithms. Findings Experimental results indicate that the proposed algorithm outperforms the BBO, PSO, DE, GA, and the ...
Salp swarm algorithm (SSA) is a unique swarm intelligent algorithm widely used for various practical applications due to its simple framework and good optimization performance. However, like other swarm-based algorithms, SSA yields local optimal solutions and has a slow convergence rate and low soluti...