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A firefly algorithm for the design of force and placement of friction dampers for control of man-induced vibrations in footbridges

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OPTIMIZATION AND ENGINEERING 2015年第3期16卷 633-661页

作者： Fadel Miguel, Leticia Fleck Fadel Miguel, Leandro Fleck Lopez, Rafael Holdorf Univ Fed Rio Grande do Sul Dept Mech Engn Porto Alegre RS Brazil Univ Fed Santa Catarina Dept Civil Engn Florianopolis SC Brazil

It is known that the use of passive energy dissipation devices, as friction dampers, reduces significantly the dynamic response of structures subjected to dynamic actions. However, the parameters of each damper as well as the best placement of these devices remain difficult to determine. Although some studies on optimization of tuned mass damper and viscous/viscoelastic dampers are being developed, works on optimum use of friction dampers is still lacking. Thus, in this paper, the simultaneous optimization of force and placement of friction dampers is proposed. To solve this optimization problem, the recently developed firefly algorithm is employed, which is able to deal with non-convex optimization problems, involving mixed discrete and continuous variables. For illustration purposes, two common footbridges are analyzed, in which the cost function is to minimize the maximum acceleration of the structures, whereas forces and positions of friction dampers are the design variables. The results showed that the proposed method was able to determine the optimum friction forces of each damper as well as their best positions in the structures. The maximum acceleration was reduced in more than 95 % for the Warren truss footbridge, with three friction dampers, and in more than 92 % for the Pratt truss footbridge, with only two friction dampers. In addition, the proposed methodology is quite general and it is believed that it can be recommended as an effective tool for optimum design of friction dampers for structural response control. Thus, this paper shows that the design of friction dampers can be done in a safe and economic way.

关键词： Friction dampers optimization Dynamic problem optimization firefly algorithm Mixed discrete and continuous variables Passive vibration control Man-induced vibrations Footbridges

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Classifier ensemble reduction using a modified firefly algorithm: An empirical evaluation

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EXPERT SYSTEMS WITH APPLICATIONS 2018年 93卷 395-422页

作者： Zhang, Li Srisukkham, Worawut Neoh, Siew Chin Lim, Chee Peng Pandit, Diptangshu Univ Northumbria Fac Engn & Environm Dept Comp Sci & Digital Technol Computat Intelligence Res Grp Newcastle Upon Tyne NE1 8ST Tyne & Wear England UCSI Univ Fac Engn Technol & Built Environm Kuala Lumpur 56000 Malaysia Deakin Univ Inst Intelligent Syst Res & Innovat Waurn Ponds Vic 3216 Australia

In this research, we propose a variant of the firefly algorithm (FA) for classifier ensemble reduction. It incorporates both accelerated attractiveness and evading strategies to overcome the premature convergence problem cif the original FA model. The attractiveness strategy takes not only the neighboring but also global best solutions into account, in order to guide the firefly swarm to reach the optimal regions with fast convergence while the evading action employs both neighboring and global worst solutions to drive the search out of gloomy regions. The proposed algorithm is subsequently used to conduct discriminant base classifier selection for generating optimized ensemble classifiers without compromising classification accuracy. Evaluated with standard, shifted, and composite test functions, as well as the Black-Box Optimization Benchmarking test suite and several high dimensional UCI data sets, the empirical results indicate that, based on statistical tests, the proposed FA model outperforms other state-of-the-art FA variants and classical metaheuristic search methods in solving diverse complex unimodal and multimodal optimization and ensemble reduction problems. Moreover, the resulting ensemble classifiers show superior performance in comparison with those of the original, full-sized ensemble models. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Ensemble reduction Classification firefly algorithm

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Inverse identification of modified Johnson-Cook model for cutting titanium alloy Ti6Al4V using firefly algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2020年第3期234卷 584-599页

作者： Zhou, Jinhua Ren, Junxue Jiang, Yong Northwestern Polytech Univ Sch Mech Engn Minist Educ Key Lab Contemporary Design & Integrated Mfg Tech Xian 710072 Shaanxi Peoples R China Guilin Hengda Min Machinery Co Ltd Guilin Peoples R China

The original Johnson-Cook equation fails to describe the significant thermal softening phenomenon of flow stress in cutting process of titanium alloy Ti6Al4V. Recently, some researchers developed some modified Johnson-Cook models of Ti6Al4V by introducing some additional parameters. But effective parameter identification method is unavailable in those research works. In this work, an inverse approach is developed to determine the additional parameters. A modified Johnson-Cook model with the hyperbolic tangent function is adopted, in which four unknown parameters need to be determined. The parameter assessment is taken as an optimization process based on the unequal division parallel-sided shear zone model. Along with the measured cutting force and chip thickness, the firefly algorithm is introduced to search for the parametric optimal solution. Those four parameters are determined when the difference between the predicted and experimental effective stress at shear plane reaches its minimum. The identified constitutive model is subsequently verified by finite element simulation of orthogonal cutting process, and compared with previous different material models. With the identified modified Johnson-Cook model, the serrated chip is observed in all the simulations. A good agreement between verification experiments and simulations is achieved. An acceptable prediction accuracy with an error of 10.28% on cutting force and an error of 18.12% on chip size is achieved.

关键词： Ti6Al4V constitutive model inverse approach firefly algorithm parallel-sided shear zone

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A novel enhanced exploration firefly algorithm for global continuous optimization problems

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ENGINEERING WITH COMPUTERS 2022年第SUPPL 5期38卷 4479-4500页

作者： Liu, Jianxun Shi, Jinfei Hao, Fei Dai, Min Zhang, Xiaoya Southeast Univ Sch Mech Engn 2 Southeast Univ Rd Nanjing 211189 Jiangsu Peoples R China Nanjing Inst Technol Sch Mech Engn Nanjing 211167 Peoples R China Guangdong Polytech Ind & Commerce Coll Mech & Elect Engn Guangzhou 510510 Peoples R China

In the global optimization process of the firefly algorithm (FA), there is a need to provide a fast convergence rate and to explore the search space more effectively. Therefore, we conduct modular analysis of the FA and propose a novel enhanced exploration firefly algorithm (EE-FA), which includes an enhanced attractiveness term module and an enhanced random term module. The attractiveness term module can improve the exploration efficiency and accelerate the convergence rate by enhancing the attraction between fireflies. The random term module improves the exploration efficiency by introducing a damped vibration distribution factor. The EE-FA uses multiple parameters to balance its exploration efficiency and convergence rate. The parameters have a great influence on the performance of the EE-FA. In order to achieve the best performance of the EE-FA, each parameter of the EE-FA needs to be simulated to determine its optimal value. Compared to multiple variants of the FA, the EE-FA has better exploration efficiency and a faster convergence speed. Experimental results reveal that the EE-FA recreated consistently vanquishes the front for 24 benchmark functions and 4 real design case studies in terms of both convergence rate and exploration efficiency.

关键词： firefly algorithm Global continuous optimization Convergence speed Damping vibration distribution

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Solution to automatic generation control problem using firefly algorithm optimized I^λD^μ controller

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ISA TRANSACTIONS 2014年第2期53卷 358-366页

作者： Debbarma, Sanjoy Saikia, Lalit Chandra Sinha, Nidul Natl Inst Technol Meghalaya Dept Elect & Elect Engn Shillong Meghalaya India Natl Inst Technol Silchar Dept Elect Engn Silchar Assam India

Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as (ID mu)-D-lambda controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (lambda) and differentiator (mu) of (ID mu)-D-lambda controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized (ID mu)-D-lambda controller gains, lambda, mu, and R are compared with that of classical integer order (10) controllers such as 1, PI and PID controllers. Simulation results show that the proposed (ID mu)-D-lambda controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized (ID mu)-D-lambda controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed (ID mu)-D-lambda controller is also tested against system parameter variations. (C) 2013 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Automatic generation control firefly algorithm Integer order controller (ID mu)-D-lambda controller

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FA-CRAN: A firefly algorithm for Dynamic BBU-RRH Mapping in Cloud/Centralized Radio Access Networks

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IEEE ACCESS 2024年 12卷 22821-22831页

作者： Imbiriba, Mariane de Paula da Silva Goncalves da Paixao, Erminio Augusto Ramos dos Santos, Albert Einstein Coutinho de Mattos Teixeira, Carlos Andre Vieira, Rafael Fogarolli Souza, Daniel da Silva Falcao, Igor Wenner Silva Cardoso, Diego Lisboa Fed Univ Postgrad Program Elect Engn BR-66075110 Belem PA Brazil Fed Univ Para Fac Comp & Technol BR-66075110 Belem PA Brazil

C-RAN (Cloud Radio Access Network) is an architecture designed to the new generation of mobile networks. It has handled many problems arising from the 4-generation network, and made several improvements, such as centralized processing and energy efficiency, among others. However, time-varying traffic, known as the tidal effect, impairs the network by making resource allocation less efficient, and this affects network performance in terms of problems related to blocked users and power consumption. This study seeks to evaluate an optimized mapping model between RRH (Remote Radio Head) and BBU (Base Band Unit) by providing a fairer and more efficient load balancing. In addition, this solution is compared with some key algorithms used in the literature for addressing optimization problems. The results demonstrated that, owing to its effective search feature, the firefly algorithm, was the most promising system, since it obtained better performance measures than the others.

关键词： C-RAN balancing firefly algorithm

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Chaos firefly algorithm With Self-Adaptation Mutation Mechanism for Solving Large-Scale Economic Dispatch With Valve-Point Effects and Multiple Fuel Options

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IEEE ACCESS 2018年 6卷 45907-45922页

作者： Yang, Yude Wei, Bori Liu, Hui Zhang, Yiyi Zhao, Junhui Manla, Emad Guangxi Univ Guangxi Key Lab Power Syst Optimizat & Energy Tec Nanning 530004 Peoples R China Univ New Haven Dept Elect & Comp Engn & Comp Sci West Haven CT 06516 USA

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The effectiveness of the CMFA method to solve economic dispatch problems with high nonlinearities is demonstrated using five classic test power systems. The solutions obtained are compared with the results of the original algorithm and several methods of optimization proposed in the previous literature. The high performance of the CMFA algorithm is demonstrated by its ability to achieve search solution quality and reliability, which reflected in minimum total cost, convergence speed, and consistency.

关键词： Economic dispatch firefly algorithm multiple fuel options valve-point effects

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An improved chaotic firefly algorithm for global numerical optimization

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2019年第1期12卷 131-148页

作者： Brajevic, Ivona Stanimirovic, Predrag Univ Nis Dept Math & Comp Sci Fac Sci & Math Visegradska 33 Nish 18000 Serbia Business Acad Univ Fac Appl Management Econ & Finance Jevrejska 24 Belgrade 11000 Serbia

firefly algorithm (FA) is a prominent metaheuristc technique. It has been widely studied and hence there are a lot of modified FA variants proposed to solve hard optimization problems from various areas. In this paper an improved chaotic firefly algorithm (ICFA) is proposed for solving global optimization problems. The ICFA uses firefly algorithm with chaos (CFA) as the parent algorithm since it replaces the attractiveness coefficient by the outputs of the chaotic map. The enhancement of the proposed approach involves introducing a novel search strategy which is able to obtain a good ratio between exploration and exploitation abilities of the algorithm. The impact of the introduced search operator on the performance of the ICFA is evaluated. Experiments are conducted on nineteen well-known benchmark functions. Results reveal that the ICFA is able to significantly improve the performance of the standard FA, CFA and four other recently proposed FA variants.

关键词： firefly algorithm chaos global optimization nature-inspired algorithms exploitation exploration

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RETRACTED: Application of firefly algorithm on optimal power flow control incorporating simplified impedance UPFC model (Retracted article. See vol. 83, pg. 603, 2016)

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 71卷 358-363页

作者： Manoranjitham, Emily G. Alagarsamy, Shunmugalatha SACS MAVMM Engn Coll Madurai Tamil Nadu India Velammal Coll Engn & Technol Madurai Tamil Nadu India

This paper proposes an algorithm to solve optimal power flow (OPF) in power system which has a unified power flow controller (UPFC). This UPFC can improve power transfer capability and transient stability and can reduce the transmission loss and fuel cost of generation. In this paper a new and simplified model of UPFC based on circuit elements for enhancing power flow is presented. Several power flow models of UPFC which are discussed in the literature require complex program codes for computing power injections. Further modification of Jacobian matrix and load flow program structure is a major problem. To reduce these complexities an alternative model of UPFC is proposed and in this model the power injected by the series converter is designed as negative impedance. In order to overcome the nonlinearity of OPE problem it is essential to use a heuristic algorithm. As a result in this paper a firefly algorithm (FFA) to solve the OPF problem is presented. Significantly, firefly algorithm is very efficient in dealing with multimodal global optimization problems. The proposed model is developed with two bus system and the firefly algorithm is tested with standard IEEE 30 bus network using Matlab. The firefly algorithm approach can obtain better solutions than other optimization algorithms. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Component UPFC Negative impedance model Optimal power flow firefly algorithm

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A multi-strategy firefly algorithm based on rough data reasoning for power economic dispatch

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第9期19卷 8866-8891页

作者： Zhou, Ning Zhang, Chen Zhang, Songlin Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Peoples R China

Dynamic economic dispatch (DED) is a multi constraint and nonlinear complex problem, which is embodied in the dynamic decision-making coupled with each other in time and space. It is generally transformed into a high-dimensional multi constraint optimization problem. In this paper, a multi Strategy firefly algorithm (MSRFA) is proposed to solve the DED problem. MSRFA puts forward three strategies through the idea of opposite learning strategy and rough data reasoning to optimize the initialization and iteration process of the algorithm, improve the convergence speed of the algorithm in medium and high dimensions, and improve the escape ability when the algorithm falls into local optimization;The performance of MSRFA is tested in the simulation experiment of DED problem. The experimental results show that MSRFA can search the optimal power generation cost and minimum load error in the experiment, which reflects MSRFA superior stability and ability to jump out of local optimization. Therefore, MSRFA is an efficient way to solve the DED problem.

关键词： power system dynamic economic dispatch firefly algorithm opposing learning strategies rough data reasoning relational reasoning

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