In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

The following study deals with the updating the finite element model of structures using the operational modal analysis. The updating process uses an evolutionary optimization algorithm, namely bees algorithm which applies instinctive behavior of honeybees for finding food sources. To determine the uncertain updated parameters such as geometry and material properties of the structure, local and...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. Various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper, a new binary version of the ABC algorithm inspired by quantum computing calle...

Autonomous systems assume intelligent behaviour with capabilities of dealing in complex and changing environments. Problem of path planning, which can be observed as an optimization problem, seems to be of high importance for arising of intelligent behaviour for different real-world problem domains. Swarm intelligence has gained increasingly high interest among the researchers from different ar...

The Artificial Bee Colony is a swarm based meta-heuristic algorithm for optimizing numerical based problem and provides the solution with accuracy and less effort, cost, time and space. Here the word meta heuristic means to provide a better solution to the given problem especially in the case of incomplete or imperfect information. In ABC algorithm, bees search best food source from many food s...

this paper presents a fault location technique for transmission lines with minimum current measurement. this algorithm investigates proper current ratios for fault location problem based on thevenin theory in faulty power networks and calculation of short circuit currents in each branch. these current ratios are extracted regarding lowest sensitivity on thevenin impedance variations of the netw...

This paper presents a novel version of the bees algorithm. This version is characterized by an extended set of search operators, and a mechanism that protects the most recently generated solutions from competition with more evolved individuals. Compared to the standard implementation of the bees algorithm, the new procedure requires the selection of an additional set of parameters. A new statis...

Correction to: Chapter “Bees Algorithm Models for the Identification and Measurement of Tool Wear” in: D. T. Pham Hartono (eds.), Intelligent Production Manufacturing Optimisation–The Bees Approach, Springer Series in Advanced Manufacturing, https://doi.org/10.1007/978-3-031-14537-7_7

Bee colony optimization (BCO) is one of the most recent algorithms in swarm intelligence that can be used in optimization problems this algorithm is based on the intelligent behavior of honey bees in foraging process. In this paper bee colony optimization is applied to solve the task scheduling problem which tasks have dependency with each other. Scheduling of tasks that represents by directed ...

In this paper, Artificial Bee Colony (ABC) algorithm which inspired from the behavior of honey bees swarm is presented. ABC is a stochastic population-based evolutionary algorithm for problem solving. ABC algorithm, which is considered one of the most recently swarm intelligent techniques, is proposed to optimize least square support vector machine (LSSVM) to predict the daily stock prices. The...