Mass optimization on shape and sizing with multiple natural frequency constraints are highly nonlinear dynamic optimization problems. Multiple natural frequency constraints normally cause difficult dynamic sensitivity analysis and, in addition, two different types of design variables, nodal coordinates and crosssectional areas, often lead to divergence. Thus, the choice of the appropriated meth...

An improved hybrid firefly algorithm with probability attraction model (IHFAPA) is proposed to solve the problems of low computational efficiency and accuracy in solving complex optimization problems. First, method square-root sequence was used generate initial population, so that population had better diversity. Second, an adaptive probabilistic attract fireflies according brightness level fir...

Optimization problem is one of the most difficult and challenging problems that has received considerable attention over the last decade. Researchers have been constantly investigating better ways to solve it. Recently, one optimization technique called firefly algorithm has gained the interest of many researchers. This algorithm is a type of swarm intelligence algorithm based on the reaction o...

Wireless Sensor Networks (WSNs) consist of several sensor nodes, each which may collect, receive and transmit data. In recent years, WSNs have emerged as essential technologies due to their ubiquity in applications such the military, smartphones, disaster management, healthcare monitoring, other surveillance systems. The inability send data from node promptly impossibility new reaching node's q...

The approach described in this paper uses evolutionary algorithms to create multiple-beam patterns for a concentric circular ring array (CCRA) of isotropic antennas using common set excitation amplitudes. flat top, cosec2, and pencil beam are examples patterns. All these designs have an upward angle θ = 0◦. the further created three azimuth planes (φ 0◦, 5◦, 10◦). To necessary patterns, non-uni...

The idea of smart grids has created new opportunities in the electrical networks for monitoring the system status. One of the valuable and significant techniques for monitoring the smart grids is state estimation. In this way, this paper proposes a sufficient state estimation algorithm for inclusive monitoring of the distribution systems in the presence of RESs (renewable energy sources). The p...

Early prediction of thermal loads plays an essential role in analyzing energy-efficient buildings’ energy performance. On the other hand, stochastic algorithms have recently shown high proficiency dealing with this issue. These are reasons that study is dedicated to evaluating innovative hybrid method for predicting cooling load (CL) buildings residential usage. The proposed model a combination...

Recent studies have witnessed remarkable merits of metaheuristic algorithms in optimization problems. Due to the significance early analysis thermal load energy-efficient buildings, this work introduces and compares four novel optimizer techniques—the firefly algorithm (FA), optics-inspired (OIO), shuffled complex evolution (SCE), teaching–learning-based (TLBO)—for an accurate prediction heatin...

The paper proposes a novel evolutionary optimization approach of solving a multi-robot stick-carrying problem. The problem refers to determine the time-optimal trajectory of a stick, being carried by two robots, from a given starting position to a predefined goal position amidst static obstacles in a robot world-map. The problem has been solved using a new hybrid evolutionary algorithm. Hybridi...