Modified cuckoo search algorithm for the optimal placement of actuators problem

Display Omitted We presented a novel modified cuckoo search algorithm (NMCSA) for optimal placement of actuators problems.The proposed NMCSA employs a novel adaptive strategy to balance exploration and exploitation, which lead to achieve a more rapid and efficient algorithm.Actuators located in positions determined by proposed algorithm can effectively reduce control spillover.The NMCSA is compared with state-of-the algorithms and their variants. Computational results show that the NMCSA outperforms with many other metaheuristics in the literature. This paper proposes a novel modified cuckoo search algorithm (NMCSA) to solve optimal placement of actuators (OPA) for active vibration control. The purpose of OPA is to minimize control spillover effect and maximize the control force applied to the desired modes. To achieve this objective, NMCSA first employs speed factor (SFR) and aggregation factor (AFR) for recording and analyzing the current and history information of nests. Secondly, SFR and AFR are mapped to suitable space by scale conversion factors (SCF). Thus, the NMCSA based on SCF can give adaptively actions on the step size and discovery probability pa to balance exploration and exploitation. The performance of NMCSA is confirmed by some well-known benchmark functions. Subsequently, the NMCSA is applied to solve OPA and compared with several state-of-the-art algorithms in the literature, the statistical results demonstrate that the proposed algorithm has a higher convergence speed and better search ability.