R. Rajendra, "Particle Swarm Optimization Algorithm vs Genetic Algorithm to Develop Integrated Scheme for Obtaining Optimal Mechanical Structure and Adaptive Controller of a Robot," Intell. Control Autom., vol. 02, no. November, pp. 430-449, 2011.R. Rajendra and D. K. Pratihar, "Particle ...
Ludwig, S.A., Schoene, T. (2012). Matchmaking in Multi-attribute Auctions using a Genetic Algorithm and a Particle Swarm Approach. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds) New Trends in Agent-Based Complex Automated Negotiations. Studies in Computational Intel...
using structural search process and can optimize for new solutions under change (Shabani et al., 2020), however it can be a bit on the slower end when it comes to solving simple problems and needs more validation in real time IoT networks. The Slime Mould Algorithm (SMA) ...
This paper introduces a modified version of a genetic algorithm with aggressive mutation (GAAM), one of the genetic algorithms (GAs) used for feature selec
Introducing the genetic algorithm; Exploring whether genetic algorithms are better than simulated annealing; Solving the “Packing to Mars” problem with genetic algorithms; Solving TSP and assigning deliveries to trucks with genetic algorithms; Creating
Various optimization techniques have been applied in task scheduling such as genetic algorithm, Electro search, ant colony optimization, simulated annealing, tabu search, particle swarm optimization. Because of the tremendous computing power required for executing real-time scientific workflow, it is hard...
Particle Swarm Optimization (PSO) [50] using multi-objective optimization technique has been designed for efficient IoT service placement in fog-enabled networks. The proposed algorithm focuses on minimizing service cost, response time, and maximizing fog resource utilization and throughput by using a ...
methods based on the one-logarithmic-decade apart16or the direct fit approach using a global optimization algorithm15. For such a complex problem, the particle swarm optimization (PSO) algorithm also can be used35,36,37. Related to non-linear viscoelastic materials, Barrientos et al. proposed ...
Microcavities enable the generation of highly efficient microcombs, which find applications in various domains, such as high-precision metrology, sensing, and telecommunications. Such applications generally require precise control over the spectral featu
The algorithm is quite effective, but a number of variations have been proposed to improve its performance. In this paper, a new adaptive fractional-order (FO) genetic-particle swarm optimization (FOGPSO) version is proposed. The FOGPSO associates the particle selection operations of a genetic ...