This research work intends to propose a system with improved cuckoo search based robust ensemble co-clustering algorithm (ICS RECCA) for enzyme clustering. The cuckoo search algorithm has been inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host birds can engage direct conflict with the intruding cuc...

The cuckoo search algorithm is a novel metaheuristic based on the reproduction behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. It has been applied to a wide range of optimization problems with good performance such as a TSP; nonetheless, it has yet to be applied to the vehicle routing problem, specifically the capacitated vehicle routi...

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...

─ Cuckoo Search (CS) is a new met heuristic algorithm. It is being used for solving optimization problem. It was developed in 2009 by XinShe Yang and Susah Deb. Uniqueness of this algorithm is the obligatory brood parasitism behavior of some cuckoo species along with the Levy Flight behavior of some birds and fruit flies. Cuckoo Hashing to Modified CS have also been discussed in this paper. CS ...

optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

K-means algorithm is a well-known clustering algorithm. In spite of its advantages such as high speed and ease of employment, this algorithm suffers from the problem of local optima. In order to overcome this problem, a lot of works have been carried out on clustering. This paper presents a hybrid extended cuckoo optimization algorithm (ECOA) and K-means (K) algorithm called ECOA-K. The COA alg...

In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more...

This paper presents an object-oriented software system that implements a cuckoo search (CS) metaheuristic for unconstrained optimization problems. Yang and Deb developed cuckoo search algorithm in MATLAB and tested it on some standard benchmark functions as well as on some engineering optimization problems where it showed promising results. We developed our algorithm in JAVA programming languag...

Nature-inspired metaheuristic algorithms have attracted much attention in the last decade, and new algorithms have emerged almost every year with a vast, ever-expanding literature. In this chapter, we briefly review two latest metaheuristics: bat algorithm and cuckoo search for global optimization. Bat algorithm was proposed by Xin-She Yang in 2010, inspired by the echolocation of microbats, wh...

Cuckoo Search (CS) algorithm is a metaheuristic optimization algorithm developed by Xing-she Yang and Suash Deb in 2009. This paper explores the various research work done in application of Cuckoo Search algorithm in optimization of geometry, processes, signals and systems in real world engineering problems. Various researchers have applied Cuckoo Search algorithm in the following broad domains...