A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages ...

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...

Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0-1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a no...

In this paper, a Cuckoo Search Algorithm (CSA) is proposed for solving environmental economic load dispatch (EELD) problem with quadratic fuel function. Cuckoo Search is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems with promising results. ...

Clustering of web search result document has emerged as a promising tool for improving retrieval performance of an Information Retrieval (IR) system. Search results often plagued by problems like synonymy, polysemy, high volume etc. Clustering other than resolving these problems also provides the user the easiness to locate his/her desired information. In this paper, a method, called WSRDC-CSCC...

Here, metaheuristic search techniques are applied for robotic path planning. Robot has to move from its starting point called source point to final point called as destination point with minimum number of moves and iteration. Here both cuckoo search and bat algorithms are applied for the proposed problem and simulation results are compared. The techniques are applied for different number of pop...

The World Wide Web serves as a huge widely distributed global information service center. The tremendous amount of information on the web is improving day by day. So, the process of finding the relevant information on the web is a major challenge in Information Retrieval. This leads the need for the development of new techniques for helping users to effectively navigate, summarize and organize ...

Nature inspired meta-heuristic algorithms are iterative search processes which find near optimal solutions by efficiently performing exploration and exploitation of the solution space. Considering the solution space in a specified region, this work compares performances of Bat, Cuckoo search and Firefly algorithms for unconstrained optimization problems. Global optima are found using various te...

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...