On Honey Bees and Dynamic Server Allocation in Internet Hosting Centers
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Particle swarm approach for structural design optimization
Computers and Structures
Journal of Global Optimization
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Truss optimization with dynamic constraints using a particle swarm algorithm
Expert Systems with Applications: An International Journal
Nature-Inspired Metaheuristic Algorithms: Second Edition
Nature-Inspired Metaheuristic Algorithms: Second Edition
Weight minimization of trusses with genetic algorithm
Applied Soft Computing
Artificial Bee Colony algorithm for optimization of truss structures
Applied Soft Computing
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
Shape and size optimisation of structures combining different types of constraints normally causes difficult sensitivity analysis. Thus, choosing the appropriate method to solve this kind of problem is of paramount importance. There are many metaheuristic methods and new ones continue being developed. An assessment of these algorithms may help to choose one. In this paper, three recent metaheuristic algorithms, harmony search HS, artificial bee colony ABC and firefly algorithm FA, are evaluated. The effectiveness of these methods are demonstrated by solving seven benchmark structural optimisation problems. Additionally, the optimisation of a realistic transmission tower is performed, which may serve as benchmark to validate new optimisation methods. A parametric study was also carried out and the statistical results were presented. The results showed that the three algorithms reached, in a relatively low computational time, better results than most literature, emphasising their excellent ability. Comparisons among the algorithms could be established.