• Title/Summary/Keyword: The Bees Algorithm

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The Bees Algorithm with Weighted Sum Using Memorized Zones for Multi-objective Problem

  • Lee, Ji-Young;Oh, Jin-Seok
    • Journal of Advanced Marine Engineering and Technology
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    • v.33 no.3
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    • pp.395-402
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    • 2009
  • This paper presents the newly developed Pareto-based multi-objective Bees Algorithm with weighted sum technique for solving a power system multi-objective nonlinear optimization problem. Specifically, the Pareto-based Bees Algorithm with memorized zone has been developed to alleviate both difficulties from classical techniques and intelligent techniques for multi-objective problems (MOP) and successfully applied to an Environmental/Economic (electric power) dispatch (EED) problem. This multi-objective Bees Algorithm has been examined and applied to the standard IEEE 30-bus six-generator test system. Simulation results have been compared to those obtained using other approaches. The comparison shows the potential and effectiveness of the proposed Bees Algorithm for solving the multi-objective EED problem.

The Dynamic Allocated Bees Algorithms for Multi-objective Problem

  • Lee, Ji-Young;Oh, Jin-Seok
    • Journal of Advanced Marine Engineering and Technology
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    • v.33 no.3
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    • pp.403-410
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    • 2009
  • The aim of this research is to develop the Bees Algorithm named 'the dynamic allocated Bees Algorithm' for multi-objective problem, especially in order to be suit for Pareto optimality. In addition two new neighbourhood search methods have been developed to produce enhanced solutions for a multi-objective problem named 'random selection neighbourhood search' and 'weighted sum neighbourhood search' and they were compared with the basic neighbourhood search in the dynamic allocated Bees Algorithm. They were successfully applied to an Environmental/Economic (electric power) dispatch (EED) problem and simulation results presented for the standard IEEE 30-bus system and they were compared to those obtained using other approaches. The comparison shows the superiority of the proposed dynamic allocated Bees Algorithms and confirms its suitability for solving the multi-objective EED problem.

On Modification and Application of the Artificial Bee Colony Algorithm

  • Ye, Zhanxiang;Zhu, Min;Wang, Jin
    • Journal of Information Processing Systems
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    • v.14 no.2
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    • pp.448-454
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    • 2018
  • Artificial bee colony (ABC) algorithm has attracted significant interests recently for solving the multivariate optimization problem. However, it still faces insufficiency of slow convergence speed and poor local search ability. Therefore, in this paper, a modified ABC algorithm with bees' number reallocation and new search equation is proposed to tackle this drawback. In particular, to enhance solution accuracy, more bees in the population are assigned to execute local searches around food sources. Moreover, elite vectors are adopted to guide the bees, with which the algorithm could converge to the potential global optimal position rapidly. A series of classical benchmark functions for frequency-modulated sound waves are adopted to validate the performance of the modified ABC algorithm. Experimental results are provided to show the significant performance improvement of our proposed algorithm over the traditional version.

An Improved Artificial Bee Colony Algorithm Based on Special Division and Intellective Search

  • Huang, He;Zhu, Min;Wang, Jin
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.433-439
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    • 2019
  • Artificial bee colony algorithm is a strong global search algorithm which exhibits excellent exploration ability. The conventional ABC algorithm adopts employed bees, onlooker bees and scouts to cooperate with each other. However, its one dimension and greedy search strategy causes slow convergence speed. To enhance its performance, in this paper, we abandon the greedy selection method and propose an artificial bee colony algorithm with special division and intellective search (ABCIS). For the purpose of higher food source research efficiency, different search strategies are adopted with different employed bees and onlooker bees. Experimental results on a series of benchmarks algorithms demonstrate its effectiveness.

Summarized IDA curves by the wavelet transform and bees optimization algorithm

  • Shahryari, Homayoon;Karami, M. Reza;Chiniforush, Alireza A.
    • Earthquakes and Structures
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    • v.16 no.2
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    • pp.165-175
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    • 2019
  • Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

Crack identification in post-buckled beam-type structures

  • Moradi, Shapour;Moghadam, Peyman Jamshidi
    • Smart Structures and Systems
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    • v.15 no.5
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    • pp.1233-1252
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    • 2015
  • This study investigates the problem of crack detection in post-buckled beam-type structures. The beam under the axial compressive force has a crack, assumed to be open and through the width. The crack, which is modeled by a massless rotational spring, divides the beam into two segments. The crack detection is considered as an optimization problem, and the weighted sum of the squared errors between the measured and computed natural frequencies is minimized by the bees algorithm. To find the natural frequencies, the governing nonlinear equations of motion for the post-buckled state are first derived. The solution of the nonlinear differential equations of the two segments consists of static and dynamic parts. The differential quadrature method along with an arc length strategy is used to solve the static part, while the same method is utilized for the solution of the linearized dynamic part and the extraction of the natural frequencies of the cracked beam. The investigation includes several numerical as well as experimental case studies on the post-buckled simply supported and clamped-clamped beams having open cracks. The results show that several parameters such as the amount of applied compressive force and boundary conditions influences the outcome of the crack detection scheme. The identification results also show that the crack position and depth can be predicted well by the presented method.

Insect-Inspired Algorithm for Zone Radius Determination of Ad-hoc Networks (곤충 행동 양식 기반의 애드 혹 네트워크를 위한 존 반경 결정 알고리즘)

  • Lee, Hea-Min;Kim, Dong-Seong
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.10
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    • pp.1079-1083
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    • 2014
  • In this paper, a new zone radius determination algorithm is proposed for a nature-inspired routing protocol that emulates the foraging behavior of bees based on their ability to find an optimal route from nectar sites. Instead of changing the radius of nodes one-hop by one-hop, the proposed algorithm alters the radius of nodes as gaps of another radius and adapt quickly to network conditions. The simulation results show that the proposed algorithm has higher efficiency compared with existing studies in an aspect of computational complexity and end-to-end delay.

Optimization Algorithms for Site Facility Layout Problems Using Self-Organizing Maps

  • Park, U-Yeol;An, Sung-Hoon
    • Journal of the Korea Institute of Building Construction
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    • v.12 no.6
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    • pp.664-673
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    • 2012
  • Determining the layout of temporary facilities that support construction activities at a site is an important planning activity, as layout can significantly affect cost, quality of work, safety, and other aspects of the project. The construction site layout problem involves difficult combinatorial optimization. Recently, various artificial intelligence(AI)-based algorithms have been applied to solving many complex optimization problems, including neural networks(NN), genetic algorithms(GA), and swarm intelligence(SI) which relates to the collective behavior of social systems such as honey bees and birds. This study proposes a site facility layout optimization algorithm based on self-organizing maps(SOM). Computational experiments are carried out to justify the efficiency of the proposed method and compare it with particle swarm optimization(PSO). The results show that the proposed algorithm can be efficiently employed to solve the problem of site layout.

MOBA based design of FOPID-SSSC for load frequency control of interconnected multi-area power systems

  • Falehi, Ali Darvish
    • Smart Structures and Systems
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    • v.22 no.1
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    • pp.81-94
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    • 2018
  • Automatic Generation Control (AGC) has functionally controlled the interchange power flow in order to suppress the dynamic oscillations of frequency and tie-line power deviations as a perturbation occurs in the interconnected multi-area power system. Furthermore, Flexible AC Transmission Systems (FACTS) can effectively assist AGC to more enhance the dynamic stability of power system. So, Static Synchronous Series Compensator (SSSC), one of the well-known FACTS devices, is here applied to accurately control and regulate the load frequency of multi-area multi-source interconnected power system. The research and efforts made in this regard have caused to introduce the Fractional Order Proportional Integral Derivative (FOPID) based SSSC, to alleviate both the most significant issues in multi-area interconnected power systems i.e., frequency and tie-line power deviations. Due to multi-objective nature of aforementioned problem, suppression of the frequency and tie-line power deviations is formularized in the form of a multi-object problem. Considering the high performance of Multi Objective Bees Algorithm (MOBA) in solution of the non-linear objectives, it has been utilized to appropriately unravel the optimization problem. To verify and validate the dynamic performance of self-defined FOPID-SSSC, it has been thoroughly evaluated in three different multi-area interconnected power systems. Meanwhile, the dynamic performance of FOPID-SSSC has been accurately compared with a conventional controller based SSSC while the power systems are affected by different Step Load Perturbations (SLPs). Eventually, the simulation results of all three power systems have transparently demonstrated the dynamic performance of FOPID-SSSC to significantly suppress the frequency and tie-line power deviations as compared to conventional controller based SSSC.