The cuckoo search algorithm is a recently developed meta-heuristic optimization algorithm, which is suitable for solving optimization problems. To enhance the accuracy and convergence rate of this algorithm, an improved cuckoo search algorithm is proposed in this paper. Normally, the parameters of the cuckoo search are kept constant. This may lead to decreasing the efficiency of the algorithm. ...

An efficient approach to solve engineering optimization problems is the cuckoo search algorithm. It is a recently developed meta-heuristic optimization algorithm. Normally, the parameters of the cuckoo search are kept constant. This may result in decreasing the efficiency of the algorithm. To cope with this issue, the cuckoo search parameters should be tuned properly. In this paper, an improved...

In this paper, Hybridization of Cuckoo Search algorithm with Powell Search (HCSPS) is used to solve optimal reactive power problem. Cuckoo search (CS) has been recently projected as a population-based optimization algorithm and it is has so far been efficaciously applied in a variety of fields. The inertia weight of Levy flights is presented to balance the capability of global and local search....

Cuckoo search (CS) has been recently proposed as a population-based optimization algorithm and it is has so far been successfully applied in a variety of fields. An efficient hybrid cuckoo search algorithm (HCSA) based on Powell direct search method is proposed for solving constrained engineering design optimization problems. The inertia weight of Levy flights is introduced to balance the abili...

For this paper, we explored the implementation of the cuckoo search algorithm applied to the capacitated vehicle routing problem. The cuckoo search algorithm was implemented with Lévy flights with the 2-opt and double-bridge operations, and with 500 iterations for each run. The algorithm was tested on the problem instances from the Augerat benchmark dataset. The algorithm did not perform well o...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

Metaheuristic algorithm is one of the most popular methods in solving many optimization problems. This paper presents a new hybrid approach comprising of two natures inspired metaheuristic algorithms i.e. Cuckoo Search (CS) and Accelerated Particle Swarm Optimization (APSO) for training Artificial Neural Networks (ANN). In order to increase the probability of the egg’s survival, the cuckoo bird...

In this paper presents the hybrid algorithm using firefly and a cuckoo search algorithm for flexible open shop scheduling problem. The flexible, open shop scheduling is known to be NP-hard. Cuckoo algorithm (CA) is one of the widely used techniques for constrained optimization. And it gave the best results compared to other algorithms. A disadvantage of cuckoo algorithm though is that they easi...

Given that the basic cuckoo search algorithm is vulnerable to local optimum and unsatisfactory calculation precision, chaotic operator (CO), employed as local algorism to optimize elitist individuals in the population, can effectively enhance the properties of cuckoo search (CS) algorithm. Tested by 15 benchmark high-dimensional functions, the experiment result indicates that chaotic cuckoo sea...

-------------------------------------------------------ABSTRACT--------------------------------------------------To Study about the Face Hallucination technique and to create high-resolution face images. After that Apply Artificial intelligence based cuckoo search technique to get high hallucination parameters. Cuckoo work on the colored image and performing face hallucination. PSNR, EPI, MOS, ...