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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Hartono, Natalia Javier Ramirez, F. Pham, D. T. Univ Birmingham Coll Engn & Phys Sci Dept Mech Engn Birmingham B15 2TT W Midlands England Univ Pelita Harapan Dept Ind Engn Tangerang Indonesia Univ Castilla La Mancha Sch Ind Engn Dept Business Adm Albacete 02071 Spain

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 Copyright (C) 2022 The Authors.

关键词： bees algorithm disassembly sequence optimisation robotics sustainability

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Optimisation of a Fuzzy Logic Controller for a Flexible Single-Link Robot Arm Using the bees algorithm

Optimisation of a Fuzzy Logic Controller for a Flexible Sing...

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7th IEEE International Conference on Industrial Informatics

作者： Pham, D. T. Kalyoncu, Mete Cardiff Univ Mfg Engn Ctr Cardiff CF24 3AA Wales

ISBN: (纸本)9781424437597

This paper focuses on using the bees algorithm to tune the scaling gains and other parameters of a fuzzy logic controller for a flexible single-link robot arm. The algorithm optimises those quantities so that the controller can move the link to a desired position with the minimum amount of vibration during the movement. Following a description of the algorithm, the paper gives the experimental results obtained for the robot demonstrating the efficiency and robustness of the design.

关键词： bees algorithm optimisation fuzzy logic controller robot flexible link

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Parameter Estimation of Essential Amino Acids in Arabidopsis thaliana Using Hybrid of bees algorithm and Harmony Search 12th

Parameter Estimation of Essential Amino Acids in Arabidopsis...

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12th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB)

作者： Aw, Mei Yee Mohamad, Mohd Saberi Chong, Chuii Khim Deris, Safaai Remli, Muhammad Akmal Ismail, Mohd Arfian Manuel Corchado, Juan Omatu, Sigeru Univ Teknol Malaysia Artificial Intelligence & Bioinformat Res Grp Fac Comp Skudai 81310 Johor Malaysia Univ Malaysia Kelantan Inst Artificial Intelligence & Big Data City Campus Kota Baharu 16100 Kelantan Malaysia Univ Malaysia Kelantan Fac Bioengn & Technol Jeli CampusLock Bag 100 Jeli 17600 Kelantan Malaysia Univ Malaysia Pahang Soft Comp & Intelligent Syst Res Grp Fac Comp Syst & Software Engn Kuantan 26300 Pahang Malaysia Univ Salamanca Biomed Res Inst Salamanca BISITE Res Grp Salamanca Spain Osaka Inst Technol Dept Elect Informat & Commun Engn Osaka 5358585 Japan

ISBN: (纸本)9783319987026;9783319987019

Mathematical models of metabolic processes are the cornerstone of computational systems biology. In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. The common way of estimating the parameters is to formulate it as an optimization problem. Global optimization methods can be applied by minimizing the distance between experimental data and predicted models. This paper proposes the Hybrid of bees algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. The performance of the BAHS is evaluated and compared with other algorithms. The results show that BAHS performed better as it improved the performance of the original BA by 60%. Meanwhile, it takes less computational time to estimate the kinetics parameters of essential amino acid production for Arabidopsis thaliana.

关键词： Systems biology Parameter estimation bees algorithm Harmony Search Computational intelligence Arabidopsis thaliana

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Balancing fuzzy multi-objective two-sided assembly lines via bees algorithm

Balancing fuzzy multi-objective two-sided assembly lines via...

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1st International Symposium on Fuzzy Systems

作者： Ozbakir, Lale Tapkan, Pinar Erciyes Univ Dept Ind Engn Kayseri Turkey

Many real life problems contain imprecise variables, constraints and objectives. Fuzzy set theory gives an opportunity to handle imprecise terms in such situations. Two-sided assembly line balancing (2sALB) problem which is a generalization of the well known simple assembly line balancing problem can also be modeled more realistically by employing fuzzy approaches. Such an approach is presented in this study to model and solve 2sALB problem by employing fuzzy mathematical programming and bees algorithm (BA). 2sALB problem is a combinatorial complex problem. For this reason BA is employed as a search mechanism for obtaining good solutions to it. BA is a relatively new member of swarm intelligence based meta-heuristics that tries to mimic natural behavior of real honey bees in food foraging in solving complex optimization problems. BA is generally applied to continuous optimization in the literature. Its application to combinatorial problems is rare. This study also presents one of the first application of BA to an assembly line balancing problem which is member of combinatorial optimization.

关键词： Fuzzy multi-objective programming two-sided assembly line balancing problem bees algorithm soft computing

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Fine-grained Task Scheduling in Cloud Data Centers Using Simulated-annealing-based bees algorithm

Fine-grained Task Scheduling in Cloud Data Centers Using Sim...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Yuan, Haitao Bi, Jing Zhou, MengChu Zhang, Jia Zhang, Wei Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA Southern Methodist Univ Dept Comp Sci Dallas TX 75275 USA Microsoft Redmond Redmond WA 98052 USA

ISBN: (纸本)9781728185262

Cloud computing is increasingly implemented by a growing number of organizations in recent years. Their critical business applications are deployed in distributed cloud data centers (CDCs) for fast response and low cost. The ever-increasing consumption of energy makes it highly important to schedule tasks efficiently in CDCs. In addition, many factors in CDCs, e.g., the wind and solar energy and prices of power grid have spatial differences. It becomes a challenging problem of how to achieve the energy cost minimization for CDCs in such a market. This work applies a G/G/1 queuing system to evaluate the optimization of servers in each CDC. Furthermore, a single-objective constrained optimization problem is given and addressed by a proposed Simulated-annealing-based bees algorithm to yield a close-to-optimal solution. Based on it, a Fine-grained Task Scheduling (FTS) algorithm is designed to minimize the energy cost of CDCs by intelligently scheduling heterogeneous tasks among distributed CDCs. In addition, it also determines running speeds of servers and the number of switched-on servers in each CDC while strictly meeting tasks' delay bounds. Realistic data-driven results demonstrate that FTS outperforms its typical benchmark scheduling peers in terms of energy cost and throughput.

关键词： Cloud data centers simulated annealing bees algorithm energy management intelligent optimization

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Optimal Design of Step – Cone Pulley Problem Using the bees algorithm 3rd

Optimal Design of Step – Cone Pulley Problem Using the Bees...

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3rd Symposium on Intelligent Manufacturing and Mechatronics, SympoSIMM 2020

作者： Yusof, Noor Jazilah Kamaruddin, Shafie Department of Materials and Manufacturing Engineering Faculty of Engineering International Islamic University Malaysia IIUM Kuala Lumpur Malaysia

ISBN: (纸本)9789811608650

Nowadays, there is a lot of optimization algorithms available to find an optimal solution in engineering problems. Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. It is commonly known as Swarm Intelligence (SI). Examples of algorithm categorized under SI are Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and the bees algorithm (BA). The bees algorithm is considered one of the recent optimization algorithms and it has been successfully solved various types of problems. It is inspired by the food foraging behavior of honeybees in nature. This study applies the bees algorithm to minimize the weight of the stepped-cone pulley in its design and satisfy the constraints. The bees algorithm is used in this study to find the optimum solution for stepped-cone pulley design and found better results compared to other optimization algorithms. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： bees algorithm Mechanical design Optimization algorithm Step-cone pulley

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A New Initialization algorithm for bees algorithm

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2nd International Multi-Conference on Artificial Intelligence Technology, M-CAIT 2013

作者： Hussein, Wasim A. Sahran, Shahnorbanun Sheikh Abdullah, Siti Norul Huda Pattern Recognition Research Group Center of Artificial Intelligence Technology Universiti Kebangsaan Malaysia 43650 Bandar Baru Bangi Malaysia

ISBN: (纸本)9783642405662

The bees algorithm (BA) is a swarm- based metaheuristic algorithm inspired by the foraging behavior of honeybees. This algorithm is very efficient, simple and natural algorithm. In this paper, two natural aspects, namely the patch environment and Levy motion are employed to propose a novel initialization algorithm to initialize the population of bees in the bees algorithm. Thus, an improved version of bees algorithm is adopted based on the proposed initialization procedure. This initialization algorithm is more natural modeling the patch environment in nature and Levy motion that is believed to characterize the foraging patterns of bees in nature. Experimental results prove the effectiveness of the proposed initialization algorithm. The obtained results confirm that the improved bees algorithm employing the proposed initialization algorithm outperforms the standard bees algorithm in terms of convergence speed and success rate. © Springer-Verlag Berlin Heidelberg 2013.

关键词： bees algorithm levy flight patch environment population initialization

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An analysis of the search mechanisms of the bees algorithm

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SWARM AND EVOLUTIONARY COMPUTATION 2020年 59卷

作者： Baronti, Luca Castellani, Marco Duc Truong Univ Birmingham Sch Comp Sci Birmingham W Midlands England Univ Birmingham Dept Mech Engn Birmingham W Midlands England

The bees algorithm has been successfully applied for over a decade to a large number of optimisation problems. However, a mathematical analysis of its search capabilities, the effects of different parameters used, and various design choices has not been carried out. As a consequence, optimisation of the bees algorithm has so far relied on trial-and-error experimentation. This paper formalises the bees algorithm in a rigorous mathematical description, beyond the qualitative biological metaphor. A review of the literature is presented, highlighting the main variants of the bees algorithm, and its analogies and differences compared with other optimisation methods. The local search procedure of the bees algorithm is analysed, and the results experimentally checked. The analysis shows that the progress of local search is mainly influenced by the size of the neighbourhood and the stagnation limit in the site abandonment procedure, rather than the number of recruited foragers. In particular, the analysis underlines the trade-off between the step size of local search (a large neighbourhood size favours quick progress) and the likelihood of stagnation (a small neighbourhood size prevents premature site abandonment). For the first time, the implications of the choice of neighbourhood shape on the character of the local search are clarified. The paper reveals that, particularly in high-dimensional spaces, hyperspherical neighbourhoods allow greater search intensification than hypercubic neighbourhoods. The theoretical results obtained in this paper are in good agreement with the findings of several experimental studies. It is hoped that the new mathematical formalism here introduced will foster further understanding and analysis of the bees algorithm, and that the theoretical results obtained will provide useful parameterisation guidelines for applied studies.

关键词： bees algorithm Optimisation Statistical analysis

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Optimisation of robotic disassembly plans using the bees algorithm

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2022年第0期78卷

作者： Hartono, Natalia Ramirez, F. Javier Pham, D. T. Univ Birmingham Dept Mech Engn Birmingham B15 2TT England Univ Castilla La Mancha Sch Ind Engn Campus Univ S-N Albacete 02071 Spain Univ Pelita Harapan Dept Ind Engn MHThamrin Blvd 1100 Lippo Village Tangerang 15811 Indonesia

Remanufacturing is a key component of a circular economy. It enables the reduction of landfill and the preservation of natural resources, therefore benefiting the environment. Disassembly is the first stage in the remanufacturing process, but, so far, has been mostly a manual operation. Transitioning from manual to robotic disassembly is desirable in the Industry 4.0 era. A model for planning the sequence of steps a robot needs to take to dismantle a product is proposed in this study. The model has three objectives: to maximise profits, energy savings and reduction in greenhouse gas emissions. The bees algorithm, an algorithm inspired by the foraging behaviour of honey bees, was used to obtain near-optimal plans for disassembling gear pumps. Statistical tests were performed on the results obtained with different optimisation parameters to establish statistical significance. They show that the bees algorithm was able to optimise disassembly plans for profits, energy savings and reductions in greenhouse gas emissions.

关键词： bees algorithm Disassembly sequence planning Optimisation Robotic disassembly

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Nonlinear stability and optimization of thin nanocomposite multilayer organic solar cell using bees algorithm

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THIN-WALLED STRUCTURES 2020年第0期149卷 106520-000页

作者： Ngo Dinh Dat Vu Minh Anh Tran Quoc Quan Pham Truong Duc Nguyen Dinh Duc Nguyen Tat Thanh Univ NTT Inst High Technol Ho Chi Minh City Vietnam VNU Hanoi Univ Engn & Technol UET Adv Mat & Struct Lab 144 Xuan Thuy Hanoi Vietnam Univ Birmingham Sch Mech Engn Birmingham B15 2TT W Midlands England Japan Vietnam Univ VJU Infrastruct Engn Program VNU Hanoi Vietnam Japan Univ VJU Hanoi Vietnam

This paper carries out the nonlinear stability of nanocomposite multilayer organic solar cell (NMOSC) subjected to axial compressive loads. The model of organic solar cell is assumed to consist five layers: Al, P3HT:PCBM, PEDOT:PSS, IOT and Glass. Based on the classical plate theory, the basic equations are established taking into account the effect of elastic foundations and initial imperfection. The approximation solutions are selected based on the boundary conditions of the four edges of NMOSC. The equation which indicates the relationship between axial compressive loads and deflection amplitude of NMOSC is obtained by using the Galerkin method. bees algorithm is applied to maximize the value of critical buckling load with nine variables including the thickness of five layers, the length and the width of NMOSC and two stiffness coefficients of elastic foundations. The numerical results show the effect of geometrical and material parameters, initial imperfection and elastic foundations on the nonlinear static stability and the critical buckling load of NMOSC. Optimal values of nine geometrical parameters of NMOSC are also determined.

关键词： Organic solar cell Nonlinear stability Optimal design Critical buckling load bees algorithm

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