The present work describes a method for increasing software testing efficiency by identifying the optimal test sequences in the state machine diagram. The method employs a Meta-heuristic algorithm called Cuckoo Search to investigate best paths in the diagram. It tries to provide a technique for exhaustive coverage with minimal repetition which ensures all transitions coverage and all paths cove...

In the science of operation research and decision theory, selection is the most important process. Selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. The multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literatur...

This paper presents the application of a One Rank Cuckoo Search Algorithm (ORCSA) to bi-objective load dispatch (BOLD) problem where two objectives including fuel and emission are taken into consideration. ORCSA is an improvement of basic Cuckoo search algorithm (BCSA) where several modifications are carried out so as to improve the performance of the BCSA. The performance of the proposed ORCSA...

In this paper, the metaheuristics algorithm Cuckoo Search (CS), is adapted and applied for a model parameter identification of an E. coli fed-batch cultivation process. The dynamics of bacteria growth and substrate (glucose) utilization is described by a system of ordinary nonlinear differential equations. Using real experimental data set from an E. coli MC4110 fed-batch cultivation process a p...

Interest in multimodal optimization is expanding rapidly, since many practical engineering problems demand the localization of multiple optima within a search space. On the other hand, the cuckoo search (CS) algorithm is a simple and effective global optimization algorithm which can not be directly applied to solve multimodal optimization problems. This paper proposes a new multimodal optimizat...

Nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. Cuckoo Search (CS) algorithm is one of the most modern addition to the group of nature inspired optimization metaheuristics. The Simple Recurrent Networks (SRN) were initially trained by Elman with the standard back propagation (SBP) learning algorithm which is less capable and often takes en...

An effective hybrid cuckoo search algorithm (CS) with improved shuffled frog-leaping algorithm (ISFLA) is put forward for solving 0-1 knapsack problem. First of all, with the framework of SFLA, an improved frog-leap operator is designed with the effect of the global optimal information on the frog leaping and information exchange between frog individuals combined with genetic mutation with a sm...

To expand the information of nest individuals, the idea of complex-valued encoding is used in cuckoo search (PCS); the gene of individuals is denoted by plurality, so a diploid swarm is structured by a sequence plurality. The value of independent variables for objective function is determined by modules, and a sign of them is determined by angles. The position of nest is divided into two parts,...

Modularity plays an important role in managing complex systems by dividing them into a set of modules that are interdependent within and independent across the modules. In response to the changing market trend of having large varieties within small production processes, modular design has assumed significant roles in the product development process. The product to be designed is represented in ...

Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where t...