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Optimal design of mechanical components using the bees algorithm

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2009年第5期223卷 1051-1056页

作者： Pham, D. T. Ghanbarzadeh, A. Otri, S. Koc, E. Cardiff Univ Mfg Engn Ctr Cardiff CF24 3AA S Glam Wales Shahid Chamran Univ Fac Engn Dept Mech Engn Ahvaz Iran

This paper describes the first application of the bees algorithm to mechanical design optimization. The bees algorithm is a search procedure inspired by the way honey bees forage for food. Two standard mechanical design problems, the design of a welded beam structure and the design of coil springs, were used to benchmark the bees algorithm against other optimization techniques. The paper presents the results obtained showing the robust performance of the bees algorithm.

关键词： bees algorithm optimization mechanical design

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Optimizing the Number of Acoustic Emission Sensors Using the bees algorithm for Detecting Surface Fractures

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Procedia CIRP 2018年 67卷 362-367页

作者： Michael S. Packianather Mark Eaton Ioannis Papadopoulos Theocharis Alexopoulos School of Engineering Cardiff University Queen's Buildings The Parade Cardiff CF24 3AA UK

Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors for detecting surface fractures and the use of the bees algorithm, a swarm-based technique, for optimizing the number of sensors required to reliably detect surface fractures. The paper describes the approach that has been used in this study where the dimension of the surface is specified by the user. The results show that, in theory and through simulation, that the bees algorithm is capable of determining the minimum number of sensors needed to locate the surface fracture with an acceptable level of accuracy. The method described could be used for the purpose of optimization in other engineering as well as non-engineering applications.

关键词： Acoustic Emission Structural Health Monitoring bees algorithm

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A sustainability-based model for robotic disassembly sequence planning in remanufacturing using the bees algorithm

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IFAC-PapersOnLine 2022年第10期55卷 1013-1018页

作者： Natalia Hartono F. Javier Ramírez D.T. Pham Department of Mechanical Engineering College of Engineering and Physical Sciences University of Birmingham B15 2TT UK and Department of Industrial Engineering University of Pelita Harapan Indonesia School of Industrial Engineering Department of Business Administration Universidad de Castilla-La Mancha 02071 Albacete Spain Department of Mechanical Engineering College of Engineering and Physical Sciences University of Birmingham B15 2TT UK

Remanufacturing, as a way to achieve the circular economy paradigm, can help save the environment by reducing the use of raw materials and energy, cutting greenhouse gas emissions and virtually eliminating the need for landfill. Disassembly is a critical first step in the remanufacturing process. This research uses the bees algorithm to optimise robotic disassembly sequence planning. Three sustainability strategies are addressed in the proposed model-based system for robotic disassembly planning: reuse, remanufacturing, and recycling. The results of two case studies based on end-of-life industrial gear pumps demonstrate that the bees algorithm can find the best solution for robotic disassembly sequence planning.

关键词： bees algorithm disassembly sequence optimisation robotics sustainability

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Using the bees algorithm to select the optimal speed parameters for wind turbine generators

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2012年第1期24卷 17-26页

作者： Fahmy, A. A. Cardiff Univ Mfg Engn Ctr Sch Engn Queens Bldg Cardiff CF24 3AA S Glam Wales

The bees algorithm is a recently developed optimization technique that mimics the foraging behavior of honey bees in nature. This study investigates the use of the bees algorithm for the selection of the optimal operating speed parameters for wind power units. Three speed parameters need to be optimized, namely, the rated, cut-in, and cut-off (furling) speed of the turbine. The aim of the optimization process is to maximize the yearly power yield and turbine usage time. The choice of the best parameters depends from the wind frequency distribution at the site of installation. Eleven locations on the coastal areas of Egypt were chosen as case studies. The well-known Particle Swarm Optimization was used as a control optimization algorithm. A popular classical approach based on the manual optimization of the sole rated speed was used as baseline for the comparison of results. The optimization of all the three speed parameters and the use of intelligent optimization techniques represent the novelties of this paper. The study showed that the bees algorithm outperformed the other two optimization methods. The proposed algorithm was able to find speed parameters that greatly enhanced the power yield, without compromising the usage time or significantly increasing the capital costs. The comparison between the standard manual optimization method and the two intelligent optimization techniques proved the superiority of the latter ones. (C) 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.

关键词： Optimization Wind turbine generator Capacity factor bees algorithm PSO Swarm intelligence

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Technological Advancements in Menstrual Health: The Role of Generative Pre-Trained Transformer and bees algorithm

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IETE JOURNAL OF RESEARCH 2024年第12期70卷 8476-8491页

作者： Irene, D. Shiny Priyadharshini, S. Indra Ponnuviji, N. P. Kalaivani, A. SRM Inst Sci & Technol Chennai India Vellore Inst Technol Sch Comp Sci & Engn Chennai India RMK Coll Engn & Technol Dept Comp Sci & Engn Puduvoyal India Sathyabama Inst Sci & Technol Sch Comp Dept Comp Sci & Engn Chennai 600 119 India

This paper introduces the concept of a smart menstrual cup, incorporating advanced technology to address challenges associated with traditional menstrual health management methods. The proposed method, Hybrid Bidirectional Encoder Generative Transformer based bees Search (Hybrid BEGT-BS), aims to enhance the longevity and reliability of smart menstrual cups. The Generative Pre-trained Transformer (GPT) is employed to extract key information and determine emotional tones related to menstruation, while the Bidirectional Encoder Representations from Transformer (BERT) classifies menstrual-related data such as cycle tracking, hygiene, and symptoms. Further different validation metrics such as F1-score, specificity, Area Under the Curve-Receiver Operating Characteristic (AUC-ROC), Mean Squared Error (MSE), recall, energy consumption, accuracy, and precision are employed to assess the method's effectiveness. From the comparative results it demonstrates the superior performance of the Hybrid BEGT-BS method in enhancing the performance of smart menstrual cups.

关键词： bees algorithm Bidirectional encoder representations from transformer Generative pre-trained transformer Initial search strategy Smart menstrual cup

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Disassembly sequence planning using discrete bees algorithm for human-robot collaboration in remanufacturing

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2020年 62卷 101860-000页

作者： Xu, Wenjun Tang, Quan Liu, Jiayi Liu, Zhihao Zhou, Zude Duc Truong Pham Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Hubei Peoples R China Wuhan Univ Technol Hubei Key Lab Broadband Wireless Commun & Sensor Wuhan 430070 Hubei Peoples R China Univ Birmingham Dept Mech Engn Birmingham B15 2TT W Midlands England

Remanufacturing helps to improve the resource utilization rate and reduce the manufacturing cost. Disassembly is a key step of remanufacturing and is always finished by either manual labor or robots. Manual disassembly has low efficiency and high labor cost while robotic disassembly is not flexible enough to handle complex disassembly tasks. Therefore, human-robot collaboration for disassembly (HRCD) is proposed to flexibly and efficiently finish the disassembly process in remanufacturing. Before the execution of the disassembly process, disassembly sequence planning (DSP), which is to find the optimal disassembly sequence, helps to improve the disassembly efficiency. In this paper, DSP for human-robot collaboration (HRC) is solved by the modified discrete bees algorithm based on Pareto (MDBA-Pareto). Firstly, the disassembly model is built to generate feasible disassembly sequences. Then, the disassembly tasks are classified according to the disassembly difficulty. Afterward, the solutions of DSP for HRC are generated and evaluated. To minimize the disassembly time, disassembly cost and disassembly difficulty, MDBA-Pareto is proposed to search the optimal solutions. Based on a simplified computer case, case studies are conducted to verify the proposed method. The results show the proposed method can solve DSP for HRC in remanufacturing and outperforms the other three optimization algorithms in solution quality.

关键词： Remanufacturing Disassembly sequence planning Human-robot collaboration Optimization problem bees algorithm

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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023年第1期340卷 117977页

作者： Jamaluddin, Jamhuri Kamarudin, Norizah Ismail, Mohd Hasmadi Ahmad, Siti Azfanizam Univ Putra Malaysia Fac Forestry & Environm Upm Serdang 43400 Selangor Malaysia Univ Putra Malaysia Fac Engn Upm Serdang 43400 Selangor Malaysia Inst Trop Forestry & Forest Prod INTROP Res Associates Upm Serdang 43400 Selangor Malaysia

Suitable extraction technique and the least cost while reducing the environmental impact is the primary concern in timber transportation planning in undulate topography. Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A bees algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m x 10 m and attributed with fixed and variable costs. The result shows the log fisher (1351 timbers) as a preferable extraction technique with total cost of RM 86,551.73 than the crawler tractor (206 timbers);the timber extraction route is 2630 m for the log fisher and 9860 m for the crawler tractor with total cost of RM 10,453.03. The model finds a suitable timber extraction technique and estimates the extraction costs. Further studies are required to compare the BA with other optimization methods for better results.

关键词： bees algorithm Forest road Timber extraction Log Fisher Crawler tractor Malaysian forest

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The SVD-enhanced bees algorithm, a novel procedure for point cloud registration

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SWARM AND EVOLUTIONARY COMPUTATION 2024年 88卷

作者： Lan, Feiying Castellani, Marco Zheng, Senjing Wang, Yongjing Univ Birmingham Dept Mech Engn Birmingham B15 2TT England Siemens Ltd China Ind Artificial Intelligence 18 Jin Fang Rd Suzhou 215127 Peoples R China

Point cloud registration entails the estimation of the rigid transformation which best aligns two point sets. At present, Iterative Closest Point is arguably the best-known and one of the most effective algorithms for point cloud registration. Iterative Closest Point uses singular value decomposition to optimise the alignment of two point sets via least squares fit. However, the algorithm is liable to converge to sub-optimal solutions due to its greedy search strategy. In this study, the problem of point cloud registration is addressed using the popular bees algorithm metaheuristic. Thanks to its global search strategy, the bees algorithm is known to be impervious to sub-optimal convergence. Singular value decomposition is used as a problem-specific operator within the bees algorithm to improve the efficiency of the search. Experimental tests showed that the standard bees algorithm outperformed Iterative Closest Point, an Evolutionary algorithm, and Particle Swarm Optimisation in terms of consistency and precision of the point cloud registration results. The bees algorithm also excelled for its robustness to noisy data. When enhanced by singular value decomposition, the bees algorithm outperformed the standard bees algorithm, and similarly enhanced evolutionary and particle swarm optimisers. The running times of the proposed method were compatible with online implementation. It is concluded that the proposed combination of bees-inspired optimisation and least squares fitting allows accurate, efficient, and consistent registration of point cloud models.

关键词： Point cloud registration Swarm intelligence bees algorithm Global registration ICP

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Fuzzy-based modeling and speed optimization of a centrifugal blood pump using a modified and constrained bees algorithm

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022年 221卷 106867-106867页

作者： Incebay, Omer Onder, Ahmet Sen, Muhammed Arif Yapici, Rafet Kalyoncu, Mete Konya Tech Univ Fac Engn & Nat Sci TR-42130 Selcuklu Konya Turkey Konya Tech Univ Tech Sci Vocat Sch Konya Turkey

Background and objective: Side effects that may occur when using blood pumps for treatment of patients are the main limitations on pump rotational speed determination. Efforts are being made to reduce side effects in both design and usage procedures. In determining the pump speed for treatment, decreasing the pressure on the main artery and preserving the valve functions are taken into consideration. In addition to these, the parameters considered for design which include pump efficiency and mechanical effects on blood cells, should also be taken into consideration. In this study, the aim is to obtain the optimum pump speed for the maximum hydraulic efficiency and minimum wall shear stresses that occur inside the pump. Methods: Blood pump modeling based on fuzzy logic is created on the hydraulic performance data of a centrifugal blood pump, whose design, CFD analysis, manufacture and experimental testing have been performed previously. Using this fuzzy logic model, the optimum pump speeds were determined using the bees algorithm, an intuitive optimization algorithm, in the operating range 1-7 L/min fluid flow rate. In the optimization process, the aim is to achieve minimum shear stress with maximal efficiency. Intravascular pressure limits (90-160 mm-Hg) were set as pressure constraints. Results: The optimum operating point is obtained as a 3350 rpm pump speed and a 4.35 L/min flow rate. At this operating point, CFD simulation is performed, and maximum wall shear stress was found to be 1458 Pa and its efficiency as 34.2%. Conclusions: In addition to the parameters commonly used in the pump speed optimization of blood pumps, the use of wall shear stresses and pump efficiency can provide certain improvements. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Blood pump Fuzzy logic bees algorithm Optimization Modeling

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bees algorithm for effective supply chains configuration

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INTERNATIONAL JOURNAL OF ENGINEERING BUSINESS MANAGEMENT 2016年 8卷 1-9页

作者： Lambiase, A. Iannone, R. Miranda, S. Lambiase, Alessandro Pham, D. T. Univ Salerno Dept Ind Engn Fisciano SA Italy Univ Birmingham Dept Mech Engn Birmingham B15 2TT W Midlands England

This article proposes a bees algorithm for solving a mathematical model of strategic supply chains planning and design in the globalization context. The model, taken from the literature, involves a multi-echelon, multi-facility and multi-product supply chain in a dynamic environment. Our bees algorithm, the first to be applied to this kind of problem, was adapted specifically to the optimization problem, and its performance was benchmarked against the genetic algorithm (GA) provided by commercial optimization software MATLAB R2011b. This is in order to test its effectiveness in an already known supply chain design problem, which has not been solved yet in optimized way. Several configurations of the algorithm were tested and analysed;the bees algorithm performs better of 10% in quality of solution respect to the GA with equivalent calculation time. The better quality of their solutions and the good calculation time performances have encouraged towards more accurate studies on tuning parameters and an extended utilization of the methodology on problems of logistic systems configuration and supply chain design.

关键词： Supply chain multi-echelon multi-facility genetic algorithm bees algorithm

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