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...

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...

This paper introduces a new hybrid algorithmic nature inspired approach based on the concepts of the Honey Bees Mating Optimization Algorithm (HBMO) and of the Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm for the Clustering Analysis, the Hybrid HBMO-GRASP, is a two phase algorithm which combines a HBMO algorithm ...

This paper proves the capability of the bees algorithm to solve complex parameter optimization problems for robot manipulator control. Two applications are presented. The first case considers the modelling of the inverse kinematics of an articulated robot arm using neural networks. The weights of the connections between the nodes need to be set so as to minimize the difference between the neura...

Optimization is the process of finding best possible solutions a problem. It has been widely used in various areas especially engineering problems. One common issues that faced by some manufacturers drilling sequences multiple holes. By holes with least total path length, manufacturer can save lot time and it increase productivity company. Thus, this study focuses on problem which solved other ...

Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to various, mostly continuous, optimization problems. For all such heuristically guided search algorithms balance between exploitation and exploration is the determining factor for success. It is generally considered that in the ABC algorithm exploitation is performed by employed ...

Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Their broad applicability, ease of use, and global perspective may be considered as the primary reason for their success. Honey bees mating process may also be considered as a typical swarm-based ap...