In addition, the neural network training algorithm compared to particle swarm optimization algorithm and the linear decreasing weight particle swarm optimization algorithm, results show that: the performance is better than the linear optimization center particle swarm decreasing weight particle swarm ...
Biswal B, Dash PK, Panigrahi BK (2009) Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization. IEEE Trans Ind Electron 56(1):212–220 Article Google Scholar Brandeau ML, Chiu SS (1989) An overview of representative problems in location re...
Multi-objective optimization using genetic algorithm FEA: Finite element analysis BOI: Body of influence DE: Differential evolution algorithm EA: Evolutionary algorithms GA: Genetic algorithm PSO: Particle swarm optimization TCA: Tooth contact analysis TSA: Thermo-elastic stress analysis 1, ...
To show the effectiveness of the proposed approach, 18 benchmark functions will be adopted for optimization via the proposed approach in comparison to existing methods. 展开 关键词: Particle swarm optimization NM simplex search hybrid optimization optimization evolutionary algorithm ...
[34] consider the fluctuation of electricity prices and propose a time-scale job scheduling algorithm for green data centers based on a genetic algorithm, simulated annealing algorithm, and particle swarm algorithm to maximize revenue. Ding et al. [35] propose a Q-learning-based job scheduling ...
In order to verify the effectiveness of GA-VMD algorithm, the VMD decomposition results based on particle swarm optimization algorithm are compared with the proposed method in this paper. Set up a set of simulation signals for analysis, and its specific expression is (9) where X is the origi...
Max-Min Particle Swarm Optimization Algorithm with Load Balancing for Distributed Task Scheduling on the Grid Environment In this paper proposes an algorithm namely max min Particle Swarm Optimization with load balancing techniques with the comparison of Swarm Intelligence Alg... C Kalpana,UK Kumar,R ...
In the proposed approach, an evolutionary algorithm based on Biogeography-Based Optimization is applied to achieve optimal task scheduling in data centers. Workloads are distributed over virtual machines in a manner that total execution time (makespan) is minimized. An Information Base Repository (IBR)...
BiTE consists of decision-making problems at two levels modeled as a multi-period bi-level optimization problem, where each decision maker optimizes one of objectives. According to the inherent complexity of bi-level programming, a co-evolutionary metaheuristic algorithm is proposed for solving BiTE....
the study of such processes at the ILC. In parallel to the exploitation of data from the Large Hadron Collider (LHC), the high-energy accelerator-based particle physics community is working towards the next large colliders after the LHC. On one hand, there is the Electron-Ion Collider (EIC...