Adaptation and hybridization typically improve the performances of original algorithm. 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 the exploration search strategies within the cuckoo search algorithm, a self-adaptation of cuckoo search control parameters and a linear population red...

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...

accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. however, due to its time variant behavior and non-linear and non-stationary nature, electricity...

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...

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extr...

This paper presents a new inspired algorithm called Quantum Inspired Cuckoo Search Algorithm (QICSA). This one is new framework relying on Quantum Computing principles and Cuckoo Search algorithm. The contribution consists in defining an appropriate representation scheme in the cuckoo search algorithm that allows applying successfully on combinatorial optimization problems some quantum computin...

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...

Modifications that introduce parallelization of standard cuckoo search algorithm are proposed in this paper. Basic form of the cuckoo search algorithm has already shown great potential for optimization problems, especially when applied to unconstrained continuous functions. In this paper two aspects of parallelization are proposed. The first one addresses the performance issue, while the second...

Gene clustering is a familiar step in the exploratory analysis of high dimensional biological data. It is the process of grouping genes of similar patterns in the same cluster and aims at analyzing the functions of gene that leads to the development of drugs and early diagnosis of diseases. In the recent years, much research has been proposed using nature inspired meta-heuristic algorithms. Cuc...