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bees metaheuristic algorithm with the aid of artificial neural networks for optimization of acid red 27 dye adsorption onto novel polypyrrole/SrFe12O19/graphene oxide nanocomposite

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POLYMER BULLETIN 2019年第12期76卷 6529-6553页

作者： Ebrahimpoor, Sodabeh Kiarostami, Vahid Khosravi, Morteza Davallo, Mehran Ghaedi, Abdol Mohammad Islamic Azad Univ Dept Chem North Tehran Branch Tehran *** Iran Islamic Azad Univ Dept Chem Gachsaran Branch Gachsaran Iran

In this work, the capability of bees-inspired algorithm with the aid of artificial neural networks (ANN-BA) for optimization of acid red 27 dye removal was studied using polypyrrole/SrFe12O19/graphene oxide (GO) as a novel nanocomposite. The nanocomposite fabricated through in situ polymerization and its characteristics were investigated by means of several instrumental techniques. The prepared polypyrrole/SrFe12O19/GO nanocomposite was employed to adsorb acid red 27 from aqueous solution. Based on the cost function as a nonlinear relation between some factors influencing the adsorption efficiency including adsorbent dosage, initial concentration, pH, shaking rate and contact time with percentage removal which were obtained by a multilayer perceptron artificial neural networks, bees metaheuristic algorithm was utilized to optimize of the batch sorption process. In addition, D-optimal response surface methodology (RSM) was also employed as a comparative study. In comparison with the D-optimal RSM, the ANN-BA model gave higher percentage removal (99%) about 4%. Under optimal conditions obtained by ANN-BA, equilibrium isotherms, kinetic behaviors and thermodynamics of the dye adsorption were thoroughly investigated. The pseudo-second-order model and the Langmuir adsorption model [with maximum capacity (q(max)) of 294.11 mg g(-1)] fitted the experimental results with the determination coefficients (R-2) of 0.94 and 0.99, respectively. The thermodynamic parameters have also been evaluated which showed the sorption procedure was endothermic and spontaneous. The findings obtained from the sorbent usage in wastewater treatment and its regeneration investigation revealed that the nanocomposite can be applied as an effective dye sorbent for removing acid red 27 dye in real samples with a reusable property.

关键词： Polypyrrole composite Graphene oxide Strontium hexaferrite Acid red 27 Artificial neural networks bees algorithm

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Robotic Assembly of Aviation Fuel Probes and Parameters Optimisation Using bees algorithm

Robotic Assembly of Aviation Fuel Probes and Parameters Opti...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Xiaoguo Lin Mo Qu Marc Auledas Noguera Ashutosh Tiwari Yongjing Wang Department of Mechanical Engineering University of Birmingham Birmingham United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Robots for automated assembly are being progressively implemented in the aerospace manufacturing sector. The dim and complex internal structure of the aircrafts significantly complicates the operation of robotic arms through visual system. This paper proposes an assembly strategy based on force-feedback control for fuel probe installation inside the aircraft wings, enabling autonomous assembly of tubular objects under translational and rotational misalignments. Furthermore, the bees algorithm (BA) is employed in a simulation environment to optimise the parameters of this control strategy. The results demonstrate that BA can effectively decrease the overall installation time while simultaneously proving the effectiveness of this method and its potential applicability in aerospace manufacturing.

关键词： bees algorithm Robotic assembly Service robots Visual systems Fuels Aircraft manufacture Probes

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Load Frequency Control of a Hybrid Power System that Uses a Fuzzy Logic Controller Tuned by the bees algorithm

Load Frequency Control of a Hybrid Power System that Uses a ...

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IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： D. U. Achilihu O. O. Oluwafunso J. A. Akinwumi Department of Electrical/ Electronics and Computer Engineering Afe Babalola University Ado-Ekiti Ekiti State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Load Frequency Control (LFC) is designed to keep system frequency close to its nominal value. This study addresses the problem of frequency variations in a hybrid power system and provides theoretically grounded remedies. These techniques are used in a hybrid power system that combines a Diesel Engine Generator (DEG) with photovoltaic (PV) arrays. A soft optimization technique using the bees algorithm (BA) is employed to fine-tune the proposed Fuzzy Logic Controller parameters for LFC, aiming for optimal control and dynamic system performance. Implementing a controller for fuzzy logic optimized by the BA, results in improved frequency response of the PV-DEG system, both during and after load disturbances. The effectiveness of the proposed method is assessed through MATLAB-Simulink simulations and tests under various load conditions. The results highlight its enhanced performance, demonstrating its effectiveness as a valuable tool for addressing challenges in electrical power systems, particularly in load frequency management. The suggested controllers were compared and the results indicate that the Fuzzy Logic Controller tuned by the BA significantly outperforms the other controllers.

关键词： Fuzzy logic bees algorithm Time-frequency analysis Prevention and mitigation Power system stability Hybrid power systems Stability analysis Transient analysis Frequency control Load modeling

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Improvement of scatter search using bees algorithm

Improvement of scatter search using Bees Algorithm

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International Conference on Signal Processing and Communication Systems, ICSPCS

作者： Ali Makki Sagheer Ahmed T. Sadiq Mohammed S. Ibrahim Computer Science Department College of Computer University of Anbar Iraq Computer Science Department University of Technology Baghdad Iraq

ISBN: (纸本)9781467323925

The Scatter Search is one of the population-based metaheuristics, which can be used to solve a wide range of problems including Traveling Salesman Problem (TSP), Routing Protocol, and End-to-End QoS, while bees algorithm can be applied to optimize the solution of these problems. In this paper, an improved Scatter Search algorithm based on bees algorithm has been presented. The improvement provides Scatter Search with random exploration for search space of problem and more of intensification for promising solutions. The original and improved Scatter Search has been tested on Traveling Salesman Problem. A computational experiment with benchmark instances is reported. The results demonstrate that the improved Scatter Search algorithm produces better performance than original Scatter Search algorithm. The developed algorithm has been compared with other algorithms for the same problem, and the result was competitive with some algorithm and insufficient with another.

关键词： component Metaheuristic Scatter Search bees algorithm Combinatorial Problems Traveling Salesman Problem travelling salesman problems Scattering Searches Bee SEARCHING algorithm

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An Enhanced bees algorithm for Multi-Hole Drill Tool Path Optimization

An Enhanced Bees Algorithm for Multi-Hole Drill Tool Path Op...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： V. P. Rathod O. P. Yadav S. P. Kadam A.P. S. Rathore Vinod Lall Department of Mechanical Engineering Government Polytechnic Thane India Department of Industrial & Systems Engineering North Carolina A & T State University Greensboro USA Department of Mechanical Engineering Government Polytechnic Vikramgad India Department of Mechanical Engineering Malaviya National Institute of Technology Jaipur India Paseka School of Business Minnesota State University Moorehead USA

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

Multi-hole drilling stands as one of the critical machining processes in various manufacturing sectors. Sequencing non-productive drill tool paths in multi-hole drilling poses a complex combinatorial challenge. Consequently, Researchers have relied on metaheuristic algorithms or their hybridized or modified versions to optimize drill tool paths. This paper utilizes a recently enhanced version of the bees algorithm (EBA), which is yet to be explored to optimize drill tool path sequencing. A well-established benchmark problem is used for optimization, and outcomes are compared with the basic version of the bees algorithm (BA) using different parameter sets. Further, it compares the outcomes with the other highly successful algorithms in the multi-hole drilling domain.

关键词： bees algorithm Drilling Sequential analysis Metaheuristics Thumb Benchmark testing Robustness Polynomials Manufacturing Kalman filters

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A novel Fibonacci-inspired enhancement of the bees algorithm: application to robotic disassembly sequence planning

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COGENT ENGINEERING 2024年第1期11卷

作者： Hartono, Natalia Pham, D. T. Univ Birmingham Mech Engn Dept Birmingham B15 2TT England Univ Pelita Harapan Ind Engn Dept Tangerang Indonesia

The bees algorithm (BA) is an intelligent, nature-inspired metaheuristic algorithm first introduced in 2005 and based on the foraging activity of honeybees. Enhancements to the BA have been made continually since its introduction, with some aimed at reducing the number of user-determined parameters. The goal is to achieve optimal results without extensive efforts required for parameter tuning. This article presents an enhanced version of the BA. The enhancement uses the Fibonacci sequence, which can be found in the family tree of the male bee (drone), to give the numbers of bees assigned to conduct local searches. The proposed BA is simple, having only four parameters that must be set by the user, as opposed to five in the basic combinatorial version. To evaluate the performance of the new algorithm in robotic disassembly sequence planning, a case study is conducted on gear pump disassembly, a commonly used benchmark problem in robotic disassembly. A comparison is made between the proposed Fibonacci bees algorithm and the Basic bees algorithm (BBA). The results are assessed using a statistical performance metric and a performance evaluation index. The findings demonstrate that the proposed algorithm is better than the BBA for more complex problems while exhibiting a similar performance on simpler tasks. Future research will explore broader applications for both continuous and combinatorial problems, demonstrating the versatility of the algorithm across different domains.

关键词： bees algorithm disassembly Fibonacci optimisation remanufacturing Zude Zhou, Wuhan University of Technology, China Operation Research Optimization Techniques Computational Techniques Design of Experiments General

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A user-friendly bees algorithm for continuous and combinatorial optimisation

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COGENT ENGINEERING 2023年第2期10卷

作者： Ismail, Asrul Harun Ruslan, Wegie Pham, Duc Truong Univ Portsmouth Ctr Operat Res & Logist Sch Math & Phys Portsmouth England Univ Birmingham Sch Engn Bees Algorithm Res Grp Birmingham England Univ Pancasila Dept Ind Engn Jakarta Indonesia Catholic Univ Indonesia Atma Jaya Dept Mech Engn Jakarta Indonesia

This paper introduces a new variant of the bees algorithm (BA) called bees algorithm with 2-parameter (BA2), which is a population-based metaheuristic algorithm designed to solve continuous and combinatorial optimisation problems. The proposed algorithm simplified the BA's parameters by combining exploration and exploitation strategies while preserving the algorithm's core principles to efficiently search for optimal solutions. The paper provides a detailed description of the algorithm's core principles and its application to two engineering problems, the air-cooling system design (ACSD) and the printed circuit board assembly sequence optimisation (PASO). The results show that BA2 outperforms previous versions of the basic BA in terms of convergence speed and solution quality. However, the authors acknowledge that further research is needed to test the scalability and generalisability of the algorithm to larger and more diverse optimisation problems. Overall, this paper provides valuable insights into the potential of metaheuristics for solving real-world optimisation problems.

关键词： bees algorithm nature-inspired algorithm bee-inspired algorithm metaheuristics continuous optimisation problem combinatorial optimisation problem

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A Novel Combination of bees and Firefly algorithm to Optimize Continuous Problems 8

A Novel Combination of Bees and Firefly Algorithm to Optimiz...

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8th International Conference on Computer and Knowledge Engineering (ICCKE)

作者： Gholami, Jafar Mohammadi, Somayeh Islamic Azad Univ Kermanshah Branch Dept Comp Engn Kermanshah Iran Islamic Azad Univ Kermanshah Sci & Res Branch Dept Comp Engn Kermanshah Iran Islamic Azad Univ Ghasr E Shirin Branch Dept Comp Engn Ghasr E Shirin Iran

ISBN: (纸本)9781538695692

Although bees algorithm (BA) has presented great performance so far in optimizing different problems, it still has weak convergence rate in some optimizations. Therefore, in this investigation in order to resolve its weakness and boost the exploitation of algorithm, it was hybridized by Firefly algorithm (FA). The hybrid bees and firefly algorithm (BA-FA) was implemented on twelve numerical benchmark functions to evaluate it. The BA-FA was also compared with four famous algorithms, including particle swarm optimization (PSO), invasive weed optimization (IWO) and so on. The results showed that BA-FA had the best performance and convergence in optimizing the mentioned functions.

关键词： bees algorithm firefly algorithm hybrid bees algorithm and firefly (BA-FA) meta-heuristic algorithm

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Adjusted Case-Based Software Effort Estimation Using bees Optimization algorithm

Adjusted Case-Based Software Effort Estimation Using Bees Op...

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15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)

作者： Azzeh, Mohammad Appl Sci Univ Fac Informat Technol Amman Jordan

ISBN: (纸本)9783642238628;9783642238635

Case-Based Reasoning (CBR) has achieved a considerable interest from researchers for solving non-trivial or ill-defined problems such as those encountered by project managers including support for software project management in predictions and lesson learned. Software effort estimation is the key factor for successful software project management. In particular, the use of CBR for effort estimation was favored over regression and other machine learning techniques due to its performance in generating reliable estimates. However, this method was subject to variety of design options which therefore has strong impact on the prediction accuracy. Selection of CBR adjustment method and deciding on the number of analogies are such two important decisions for generating accurate and reliable estimates. This paper proposed a new method to adjust the retrieved project efforts and find optimal number of analogies by using bees optimization algorithm. The bees algorithm will be used to search for the best number of analogies and features coefficient values that will be used to reduce estimates errors. Results obtained are promising and the proposed method could form a useful extension for Case-based effort prediction model.

关键词： Case-Based Reasoning Software Effort Estimation bees algorithm

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Optimal Location and Sizing of Solar Farm on Japan East Power System Using Multiobjective bees algorithm

Optimal Location and Sizing of Solar Farm on Japan East Powe...

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IEEE Energytech

作者： Prakomchai Phonrattanasak Masafumi Miyatake Orie Sakamoto Department of Electrical Engineering North Eastern University Department of Electrical Engineering Sophia University

ISBN: (纸本)9781467344456

Nowadays some nuclear power plant in Japan is shut down due to problem of security in earthquake disaster. Consequently, Japan will encounter a lack of electrical energy in the future if new electrical generation is not constructed. Solar energy is one of appropriate renewable energy for Japan. Solar panel produces electrical energy by using the natural solar radiation from sun. PV Solar farm consists of multiple components, including the photovoltaic modules, mechanical and electrical connections. PV solar farm with grid-connected can directly connect to the existing electricity grid by using inverter circuit toward transformer. In this paper, PV solar farm is utilized as a power generation which injects active power into a Japan east power system. An optimal location and sizing of solar farm by using multiobjective bees optimization (MBO) is proposed to minimize fuel and emission costs of overall system with considering solar radiation energy in each area. The results show that the proposed method found the optimal position of solar farm with minimum cost of fuel and environmental pollution.

关键词： Power system Optimization bees algorithm PV solar and Japan power system

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