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MANUFACTURING TECHNOLOGY 2021年第6期21卷 788-792页

作者： Kamaruddin, Shafie Rosdi, Mohamad Naqiuddin Sukindar, Nor Aiman Int Islamic Univ Malaysia IIUM Fac Engn Dept Mfg & Mat Engn Kuala Lumpur Malaysia

Optimization is the process of finding the best possible solutions to a problem. It has been widely used in various areas especially in engineering problems. One of the common issues that is faced by some of the manufacturers is finding drilling sequences of multiple holes. By drilling multiple holes with the least total path length, the manufacturer can save a lot of time and it can increase the productivity of the company. Thus, this study focuses on the drilling path of the multiple holes problem which has been solved by other researchers. This study uses the bees algorithm to find the best sequence of drilling holes (minimum total path length) and the results found are compared with the result of other algorithms. In addition to results comparison with other algorithms, the results obtained are verified with simulation results using MasterCAM software. The results comparison shows that the bees algorithm achieved comparable performance compared to other algorithms.

关键词： bees algorithm Optimization Drilling

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An inverse model-based bees algorithm for estimating ratio of hydraulic conductivity to drainable porosity

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JOURNAL OF HYDROLOGY 2022年 608卷 127673-127673页

作者： Mehdinejadiani, Behrouz Fathi, Parviz Khodaverdiloo, Habib Univ Kurdistan Fac Agr Dept Water Sci & Engn Sanandaj Iran Urmia Univ Dept Soil Sci Orumiyeh Iran

A major step in designing a subsurface drainage system is calculation of drainpipe spacing. Nearly, all unsteadystate drainpipe-spacing equations use ratio of hydraulic conductivity (K-s) to drainable porosity (f) in the form of kappa = K-s/f. This work developed a novel inverse model based on bees algorithm to estimate the kappa. We examined the efficiency of the developed inverse model to appraise the. using the existing data sets at laboratory and field scales. For each data set, we compared the performance of the developed inverse model with those of a dimensionless curve generated by the authors (generalized dimensionless curve), Skaggs's (1976) dimensionless curve being proportional to the data set (Skaggs's dimensionless curve), a drainpipe discharge method, and a direct method. The results showed that the best statistical indicator values were achieved for each data set when the drainage equations utilized the. deduced from the developed inverse model. All the studied techniques performed the worst for Skaggs et al.'s (1973) data at 57.5 hrs. after drainage start. For this data set, the studied techniques were, respectively, ranked as the developed inverse model, Skaggs's dimensionless curve, the generalized dimensionless curve, and the direct method. Even in this worst case, the global performance index was improved almost 93% when the drainage equation utilized the. appraised by the developed inverse model, instead of that appraised by Skaggs's dimensionless curve. The overall performance comparison of the three inverse techniques evaluated in this study revealed that the root mean square error and coefficient of determination related to the developed inverse model are the best ones, followed by those related to Skaggs's dimensionless curve, and the developed inverse model, respectively. In summary, the results revealed that, compared to the other studied techniques, the developed inverse model is the most efficient technique to estimate the., which is pro

关键词： bees algorithm Dimensionless curve Direct method Drainage discharge method Inverse model

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A Multiuser Manufacturing Resource Service Composition Method Based on the bees algorithm

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2015年第1期2015卷 1-13页

作者： Xie, Yongquan Zhou, Zude Duc Truong Pham Xu, Wenjun Ji, Chunqian Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Wuhan Univ Technol Minist Educ Key Lab Fiber Opt Sensing Technol & Informat Proc Wuhan 430070 Peoples R China Univ Birmingham Sch Mech Engn Birmingham B15 2TT W Midlands England

In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic bees algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems.

关键词： MULTIUSER computer systems MANUFACTURING resource planning bees algorithm QUALITY of service PARETO optimum

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A Novel Hybrid Method of Global Optimization Based on the Grey Wolf Optimizer and the bees algorithm

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Procedia Computer Science 2019年 150卷 471-477页

作者： S.V. Konstantinov U.K. Khamidova E.A. Sofronova RUDN University 6 Miklukho-Maklaya str. Moscow 117198 Russia Bauman Moscow State Technical University 5 2-ya Baumanskaya str. Moscow 105005 Russia Federal Research Centre "Computer Science and Control" of RAS Vavilova str. 44 b. 2 Moscow 119333 Russia

A new hybrid evolutionary algorithm based on the Grey wolf optimizer and the bees algorithm is proposed. Embedded hybridization allows combining the strengths of original methods. A comparative analysis of the new hyb... 详细信息

关键词： evolutionary algorithms hybrid algorithms bees algorithm Grey wolf optimizer

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New Technique for Global Solar Radiation Forecast using bees algorithm

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INTERNATIONAL JOURNAL OF ENGINEERING 2013年第11期26卷 1385-1392页

作者： Tolabi, H. Bagheri Moradi, M. H. Tolabi, F. Bagheri Islamic Azad Univ Fac Engn Khorramabad Branch Tehran Iran Bu Ali Sin Univ Fac Engn Hamadan Iran

Solar radiation estimation is integral part for various solar energy systems which requires precise and expensive devices to gage the solar radiation for a particular region. However, researches have proposed different techniques to estimate the solar radiation that hinder using such devices so far. Nonlinear nature and excessive dependence on the meteorological parameters of these methods forced researchers to look for quick and efficient techniques to solve related issues and find solar radiation for a particular region. In this paper, a new method based on the Angstrom model is introduced which estimates the monthly average daily global solar radiation on a horizontal surface by bees algorithm as a heuristic and population-based search technique implemented in MATLAB software. The experimental coefficients for Angstrom model are calculated for six different climate regions of Iran using proposed program written in the software. The obtained results proved the efficiency and predominance of the new method to find a more accurate level of solar radiation.

关键词： bees algorithm Global Solar Radiation Experimental Coefficients Statistical Regression Techniques Intelligent Techniques

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A new local search for the bees algorithm to optimize multiple traveling salesman problem

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INTELLIGENT SYSTEMS WITH APPLICATIONS 2023年 18卷

作者： Hamza, Ali Darwish, Ahmed Haj Rihawi, Omar Univ Aleppo Fac Informat Engn Dept Artificial Intelligence & Nat Languages Aleppo Syria

This paper presents a new local search operator with the bees algorithm (BA) to solve the Multiple Traveling Salesman Problem (MTSP), which is a kind of combinatorial optimization problem. Many algorithms and techniques were used to solve this problem;however, they could not find the optimal solutions. Some of those algorithms also have high computational costs. In this paper, the bees algorithm is adopted to form a robust optimizer with low execution time. The proposed method uses local search operators to achieve that. These operators are used to exploit the neighbors for local solutions. Many local search operators are described thoroughly. Two operators are used with the bees algorithm (BA). Then, a new local search operator called SBESTSO is proposed to improve the performance of the algorithm. The efficiency of the bees algorithm with the new local search operator was evaluated using different MTSP benchmark datasets. The results obtained were compared with those of other optimization algorithms for the same datasets. The comparisons proved the robustness of the bees algorithm in finding optimal solutions of Multiple Traveling Salesman Problems.

关键词： bees algorithm BA Combinatorial optimization problem Multiple traveling salesman problem MTSP Local operators

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Updating Finite Element Model Using Stochastic Subspace Identification Method and bees Optimization algorithm

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LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES 2018年第2期15卷 1-19页

作者： Alimouri, Pouyan Moradi, Shapour Chinipardaz, Rahim Shahid Chamran Univ Ahvaz Mech Engn Dept Ahvaz Iran Shahid Chamran Univ Ahvaz Stat Dept Ahvaz Iran

This study investigates the application of operational modal analysis along with bees optimization algorithm for updating the finite element model of structures. bees algorithm applies instinctive behavior of honeybees as they look for nectar of flowers. The parameters that needed to be updated are uncertain parameters such as geometry and material properties of the structure. To determine these uncertain parameters, local and global sensitivity analyses have been performed. An objective function is defined based on the sum of the squared errors between the natural frequencies obtained from operational modal analysis and finite element method. The natural frequencies of physical structure are determined by stochastic subspace identification method which is considered as a strong and efficient method in operational modal analysis. To verify the accuracy of this method, the proposed algorithm is implemented on a three-story structure to update parameters of its finite element model. Moreover, to study the efficiency of bees algorithm, its results are compared with those of the particle swarm optimization, and Nelder and Mead methods. The comparison indicates that this algorithm leads more accurate results with faster convergence.

关键词： Vibration analysis Finite element model updating Operational modal analysis Stochastic subspace identification bees algorithm Sensitivity analysis

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Combinational Circuit Design Using bees algorithm

Combinational Circuit Design Using Bees Algorithm

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2011 International Conference on Intelligent Computing and Integrated Systems(ICISS 2011)

作者： Nahid Mollabakhshi Mohammad Eshghi Department of Computer Engineering Science and Research Branch Islamic Azad UniversityTehran Iran ECE department Shahid Beheshti UniversityTehran Iran

In this paper a novel method to designingcombinational circuits using bees algorithm is presented. Inautomatic evolutionary design methods, the main problem isrelated to "combinatorial explosion" existing in those *** evolutionary design methods are based on "generate andtest" model, therefore with growing input numbers of digitalcircuits, the number of potential combinations which must betested are growing exponentially. To solve this problem, it isimportant to elaborate efficient decomposition techniques of thedesigned circuits to some less complex sub-circuits, and then todesign each of them independently. We present a new applicationof bees algorithm, and design and optimize combinational circuits.A computer simulation is developed to verify the performance ofthe proposed algorithm. We compared the circuits obtained by ourproposed system to the circuits designed by experienced humandesigners. In comparison to human design, our automated designshad fewer gates.

关键词： bees algorithm combinational digital circuit evolutionary algorithm

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Efficient load balancing using the bees algorithm 11

Efficient load balancing using the bees algorithm

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Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II

作者： Anabela Moreira Bernardino Eugénia Moreira Bernardino Juan Manuel Sánchez-Pérez Juan Antonio Gómez-Pulido Miguel Angel Vega-Rodríguez Computer Science and Communication Research Centre School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Department of Technologies of Computers and Communications Polytechnic School University of Extremadura Cáceres Spain

ISBN: (纸本)9783642218262

The massive growth of the Internet traffic in the last decades has motivated the design of high-speed optical networks. Resilient Packet Ring (RPR), also known as IEEE 802.17, is a standard designed for optimising the transport of data traffic over optical fiber ring networks. In this paper, we consider a Weighted Ring Arc-Loading Problem (WRALP), which arises in engineering and planning of the RPR systems. The WRALP is a combinatorial optimisation NP-complete problem. Given a set of point-to-point unidirectional traffic demands of a specified bandwidth, the demands should be assigned to the clockwise or to the counter-clockwise ring in order to yield the best performance. This paper suggests an efficient load balancing algorithm - the bees algorithm. We compare our results with nine meta-heuristics used in literature to solve the same problem. The simulation results verify the effectiveness and robustness of the bees algorithm.

关键词： bees algorithm

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bees-algorithm-BASED OPTIMIZATION OF COMPONENT SIZE AND CONTROL STRATEGY PARAMETERS FOR PARALLEL HYBRID ELECTRIC VEHICLES

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INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY 2012年第7期13卷 1177-1183页

作者： Long, V. T. Nhan, N. V. Nha Trang Univ Fac Mech Engn Khanh Hoa 650000 Vietnam

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.

关键词： Hybrid electric vehicles (HEV) bees algorithm Intelligent optimization Parallel HEV control strategy

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