Exhaustive testing is never the appropriate approach in software testing as this violates the principle of cost effectiveness in software development as well as puts time and other resources at stake. This explains the need to optimise the process of software testing. The present paper gives an overview of cuckoo search algorithm and its role in software coverage optimisation. This paper propos...

Training neural networks is a complex task that is important for supervised learning. A few metaheuristic optimization techniques have been applied to increase the effectiveness of the training process. The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. In this paper, Cuckoo search is implemented in...

Today, the information is growing enormously and it is difficult and tedious task to retrieve the necessary information from that pool. The main area for retrieving relevant answers is called intelligent information retrieval. To achieve this, question and answering system is used. This question and answering plays a major role in user query processing, information retrieval and extracting rela...

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...

Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network training. Traditional BP algorithm has some drawbacks, such as getting stuck easily in local minima and slow speed of convergence. Nature inspired meta-heuristic algorithms provide derivative-free solution to optimize complex problems. This paper pr...

This paper deals with application of evolutionary algorithm (EA) to solve optimal power flow problem in an efficient manner. In this paper a new approach using cuckoo search (CS) method is proposed for solving OPF problem by optimal setting of control variables. Cuckoo search method is a bio-inspired algorithm based on brooding behaviour of cuckoo birds. This algorithm can search for a global s...

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...

Cuckoo Search is one of the recent swarm itelligence metaheuritics. It has been succesfuly applied to a number of optimization problems, but is stil not very well researched. In this paper we present a parallelized version of the Cuckoo Search algorithm. The parallelization is implemented using CUDA architecture. The algorithm is significantly changed compared to the sequential version. Changes...

Disease forecasting using soft computing techniques is major area of research in data mining in recent years. To classify heart and diabetes diseases, this paper proposes a diagnosis system using cuckoo search optimized rough sets based attribute reduction and fuzzy logic system. The disease prediction is done as per the following steps 1) feature reduction using cuckoo search with rough set th...