M. Shahrouzi, A. Salehi,
Volume 10, Issue 1 (1-2020)
Abstract
Imperialist Competitive Algorithm, ICA is a meta-heuristic which simulates collapse of weak empires by more powerful ones that take possession of their colonies. In order to enhance performance, ICA is hybridized with proper features of Teaching-Learning-Based Optimization, TLBO. In addition, ICA walks are modified with an extra term to intensify looking for the global best solution. The number of control parameters and consequent tuning effort has been reduced in the proposed Imperialist Competitive Learner-Based Optimization, ICLBO with respect to ICA and several other methods. Efficiency and effectiveness of ICLBO is further evaluated treating a number of test functions in addition to continuous and discrete engineering problems. It is discussed and traced that balancing between exploration and exploitation is enhanced due to the proposed hybridization. Numerical results exhibit superior performance of ICLBO vs. ICA and a variety of other well-known meta-heuristics.
H. Safaeifar, M. Sheikhi Azqandi,
Volume 11, Issue 3 (8-2021)
Abstract
The impact damper is a passive method for controlling vibrations of dynamic systems. It is designed by placing one or several masses in a container, which is installed on the structure. Damping performance is affected by many parameters, such as the mass ratio of the primary structure, size, number, and material of the particles, friction and restitution coefficients of the particles and gap distance. Impact damper is effective, economical, and practical and its functionality can be further enhanced by an optimal design. In this paper, first, the mathematical modeling of a rigid impact damper used in free vibration reduction of a single degree of freedom (SDOF) system is performed. The results on this step are validated with those results of previous studies, and a good agreement is achieved. Next, the robust hybrid optimization method that is called Imperialist Competitive Ant Colony Optimization (ICACO) is introduced. After that, the damper function is optimized using ICACO, and the optimum values of the effective parameters for maximizing damping effectiveness are obtained. Comparing the results of the optimized and the basic designs shows that the optimization method is robust and the optimal results are practical. The optimum design of damper parameters using ICACO method can damp more than %94 of the system’s initial energy in a short time.
