Cuckoo Search (CS) algorithm was developed by Yang and Deb [1, 2] as an efficient population-based metaheuristic inspired by the behavior of some cuckoo species in combination with the L茅vy flight. It is also u
As an example, Layeb [27] presents a novel quantum inspired Cuckoo search algorithm (QICSA) which is a hybridization between quantum computing principles and Cuckoo search algorithm, and it can achieve better balance between exploration and exploitation. Chandrasekaran and Simon come up with a ...
An efficient optimization algorithm is critical to ensure that optimal solutions are reachable in search space17. For an example, CS algorithm outperforms PSO in achieving the global convergence. In this case, PSO algorithm converges prematurely to a local optimum (stuck in local optima predicament)...
In general, a CS algorithm can perform more powerful capacity of the global optimization by the switching/discovery probability (pa) designed for a local search [41]. For the application of the CS algorithm, it is necessary that three principal assumptions are Support vector machine (SVM) The ...
Another example is Particle Swarm Optimization (PSO) which was developed by Eberhart and Kennedy in 1995. This stochastic optimization algorithm is inspired by social behavior of bird ?ocking or ?sh schooling [3–5]. Ant Colony Optimization (ACO) is another evolutionary optimization algorithm which...
An efficient optimization algorithm is critical to ensure that optimal solutions are reachable in search space17. For an example, CS algorithm outperforms PSO in achieving the global convergence. In this case, PSO algorithm converges prematurely to a local optimum (stuck in local optima predicament)...
an application example, an UWB BPF is designed by using three base fundamental shapes; Shunt Stub (SS), Etched Square Stub (ESS) and Defected Ground Structure (DGS). SWRM and Cuckoo Search Algorithm (CSA) are utilized together in the analysis and design of the BPF. In recent years...
In particular, the cuckoo search (CS) [3] is a novel nature-inspired stochastic optimization method. This relatively new method is gaining popularity in finding the global minimum of diverse science and engineering application problems [4–8]. For example, it was recently used for the design ...
This paper proposes a novel hybrid self-adaptive cuckoo search algorithm, which extends the original cuckoo search by adding three features, i.e., a balancing of the exploration search strategies within the cuckoo search algorithm, a self-adaptation of cuckoo search control parameters and a linear...
The main goal of the present paper is to present a penalty based cuckoo search (CS) algorithm to get the optimal solution of reliability – redundancy allocation problems (RRAP) with nonlinear resource constraints. The reliability – redundancy allocation problem involves the selection of components'...