The HFC model for evolutionary computation is inspired by the stratified competition often seen in society and biology. Subpopulations are stratified by fitness. Individuals move from low-fitness subpopulations to higher-fitness subpopulations if and only if they exceed the fitness-based admission threshold of the receiving subpopulation, but not of a higher one. HFC’s balanced exploration and ...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

The traveling salesman problem (TSP) is a well-known optimization problem in graph theory, as well as in operations research that has nowadays received much attention because of its practical applications in industrial and service problems. In this problem, a salesman starts to move from an arbitrary place called depot and after visits all of the nodes, finally comes back to the depot. The obje...

Parameter identification is an important method to establish the governing system of a pumped storage unit. Appropriate parameters will make obtain better control performance. Therefore, in this study, improved artificial hummingbird algorithm (IAHA) proposed for parameter The integrates two key strategies improve optimization ability algorithm. First, Chebyshev chaotic map employed initialize ...

-The back propagation (BP) algorithm is widely used for finding optimum weights of multilayer neural networks in many pattern recognition applications. However, the critical drawbacks of the algorithm are its slow learning speed and convergence to local minima. One of the major reasons for these drawbacks is the "premature saturation'" which is a plwnomenon that the error of the neural network ...

Growing rates of premature birth have led to increases in the prevalence of retinopathy of prematurity (ROP), which is now becoming a leading cause of childhood blindness worldwide (1). At the same time, cost-effective and accessible screening methods and medical services may reduce its incidence. Prompt approaches to management of complications, as well as providing low vision aids for childre...

The present work deals with application of recently developed evolutionary computing based training methods for non-linear system identification problem. Generally, most of the systems are nonlinear in nature. The conventionally used standard derivative based identification scheme does not work satisfactorily for nonlinear systems, which is due to premature settling of the model parameters. To ...

Over the past several years, Evolutionary Computing (EC) has characterised itself to be an alternate way to search for complex computer structures. Many applications have successfully been taken into use, ranging from data mining tools to automated design of complex industrial plants or military aircraft. Several distinct types of EC have emerged during the last decade. The most prominent field...

Differential evolution algorithm is a simple yet efficient metaheuristic for global optimization over continuous spaces. However, there is a shortcoming of premature convergence in standard DE, especially in DE/best/1/bin. In order to take advantage of direction guidance information of the best individual of DE/best/1/bin and avoid getting into local trap, based on multiple mutation strategies,...