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Critical analysis: bat algorithm-based investigation and application on several domains

WORLD JOURNAL OF ENGINEERING 2021年第4期18卷 606-620页

作者： Umar, Shahla U. Rashid, Tarik A. Univ Kirkuk Dept Comp Sci & Informat Technol Kirkuk Iraq Sulaimani Polytech Univ Sulaimani Tech Coll Informat Krg Iraq Sulaimani Polytech Univ Sulaimani Tech Coll Informat Sulaimani Iraq Univ Kurdistan Hewler Sch Sci & Engn Comp Sci & Engn Dept Hewler Krg Iraq Univ Kurdistan Hewler Sch Sci & Engn Comp Sci & Engn Dept Erbil Iraq

Purpose The purpose of this study is to provide the reader with a full study of the bat algorithm, including its limitations, the fields that the algorithm has been applied, versatile optimization problems in different domains and all the studies that assess its performance against other meta-heuristic algorithms. Design/methodology/approach Bat algorithm is given in-depth in terms of backgrounds, characteristics, limitations, it has also displayed the algorithms that hybridized with BA (K-Medoids, back-propagation neural network, harmony search algorithm, differential evaluation strategies, enhanced particle swarm optimization and Cuckoo search algorithm) and their theoretical results, as well as to the modifications that have been performed of the algorithm (modified bat algorithm, enhanced bat algorithm, bat algorithm with mutation (BAM), uninhabited combat aerial vehicle-BAM and non-linear optimization). It also provides a summary review that focuses on improved and new bat algorithm (directed artificial bat algorithm, complex-valued bat algorithm, principal component analyzes-BA, multiple strategies coupling bat algorithm and directional bat algorithm). Findings Shed light on the advantages and disadvantages of this algorithm through all the research studies that dealt with the algorithm in addition to the fields and applications it has addressed in the hope that it will help scientists understand and develop it. Originality/value As far as the research community knowledge, there is no comprehensive survey study conducted on this algorithm covering all its aspects.

关键词： Swarm intelligence Bat algorithm Metaheuristic algorithms Nature-inspired algorithms optimization algorithms

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Cluster validity indices for automatic clustering: A comprehensive review

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Heliyon 2025年第2期11卷 e41953页

作者： Ikotun, Abiodun M. Habyarimana, Faustin Ezugwu, Absalom E. School of Mathematics Statistics and Computer Science University of KwaZulu-Natal King Edward Avenue Pietermaritzburg Campus KwaZulu-Natal Pietermaritzburg 3201 South Africa Unit for Data Science and Computing North-West University 11 Hoffman Street North-West Potchefstroom 2520 South Africa

The Cluster Validity Index is an integral part of clustering algorithms. It evaluates inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the quality of potential solutions. Several cluster validity indices have been suggested for both classical clustering algorithms and automatic metaheuristic-based clustering algorithms. Different cluster validity indices exhibit different characteristics based on the mathematical models they employ in determining the values for the various cluster attributes. Metaheuristic-based automatic clustering algorithms use cluster validity index as a fitness function in its optimization procedure to evaluate the candidate cluster solution's quality. A systematic review of the cluster validity indices used as fitness functions in metaheuristic-based automatic clustering algorithms is presented in this study. Identifying, reporting, and analysing various cluster validity indices is important in classifying the best CVIs for optimum performance of a metaheuristic-based automatic clustering algorithm. This review also includes an experimental study on the performance of some common cluster validity indices on some synthetic datasets with varied characteristics as well as real-life datasets using the SOSK-means automatic clustering algorithm. This review aims to assist researchers in identifying and selecting the most suitable cluster validity indices (CVIs) for their specific application areas. © 2025 The Authors

关键词： Automatic clustering Cluster validity index Clustering Metaheuristic algorithms optimization algorithms

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A combinatorial social group whale optimization algorithm for numerical and engineering optimization problems

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APPLIED SOFT COMPUTING 2021年 99卷

作者： Reddy, Aala Kalananda Vamsi Krishna Narayana, Komanapalli Venkata Lakshmi Vellore Inst Technol Sch Elect Engn Vellore 632014 Tamil Nadu India

This article presents two new hybrid swarm-human based meta-heuristic optimization algorithms benefitting from the synergy of whale optimization algorithm (WOA) and social group optimization (SGO) known as Hybrid Social Whale optimization Algorithm (HS-WOA and HS-WOA+). HS-WOA and HS-WOA+ are hybridized combining the exploratory capabilities of WOA and convergence capabilities of SGO with a perfect balance between exploration and exploitation. A comparative analysis of the new proposed hybrid algorithm is performed through various benchmark functions. Various test cases to analyze the algorithm's performance like influence of population size, effect of dimensionality, effect of iterative count is performed and compared. The proposed algorithms are compared with modern-meta-heuristics and variants of WOA and SGO to justify its performance. The performance is evaluated statistically through the Wilcoxon's rank-sum test and Friedman's non-parametric test while the convergence curves and acceleration rates are provided to demonstrate the convergence capabilities of the proposed hybrid algorithms and the computational times are recorded to showcase the computational speeds of all the algorithms used in comparison. Composite benchmarking functions are considered to analyze the exploratory prowess and the algorithms' capability to avoid local entrapment. To assess and evaluate the performance of the proposed algorithms with real world optimization tasks, four standard engineering problems with penalty constraints are added to the test bench. Further, a multi-unit production planning problem with correction constraints is deployed through the proposed algorithms. The benchmarking results prove that HS-WOA and HS-WOA+ s' performance is competitive and better than the various algorithms tested against and had a statistically significant performance with lower computational times. The algorithms performed well for both standard engineering problems and the multi-unit productio

关键词： Hybrid Social Whale optimization Algorithm (HS-WOA) HS-WOA Whale optimization Algorithm (WOA) Social Group optimization (SGO) Meta-heuristics optimization algorithms Global optimization Benchmark functions Standard engineering problems Multi-unit production planning

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MODELLING AND PARAMETER IDENTIFICATION FOR A FLEXIBLE ROTOR WITH PERIODIC IMPACTS 17

MODELLING AND PARAMETER IDENTIFICATION FOR A FLEXIBLE ROTOR ...

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ASME International Design Engineering Technical Conferences / 42nd Annual Computers and Information in Engineering Conference (IDETC-CIE) / 17th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC)

作者： Holzinger, Stefan Schieferle, Manuel Gerstmayr, Johannes Hofer, Manfred Gutmann, Christoph Univ Innsbruck Innsbruck Austria STIHL Tirol GmbH Langkampfen Austria

ISBN: (纸本)9780791885468

The ability of a multibody dynamics model to accurately predict the behavior of a real system depends heavily on the correct choice of model parameters. The identification of unknown system parameters, which cannot be directly computed or measured is usually time consuming and costly. If experimental measurement data of the real system is available, the parameters in the mathematical model can be determined by minimizing the error between the model response and the measurement data. The latter task can be solved by means of optimization. While many optimization methods are available, optimization with a genetic algorithm is a promising approach for searching optimal solutions for complex engineering problems, as reported in a paper of one of the authors. So far, however, there is no general approach how to apply genetic optimization algorithms for complex multibody system dynamics models in order to obtain unknown parameters automatically - which is however of great importance when dealing with real flexible multibody systems. In the present paper we present a methodology to determine several unknown system parameters applied to a flexible rotor system which is excited with periodic impacts. Experiments were performed on the physical system to obtain measurement data which is used to identify the impact force as well as the support stiffnesses of the rotor system using genetic optimization.

关键词： Rotors Modeling optimization Multibody systems Dynamics (Mechanics) Errors Genetic algorithms optimization algorithms Multibody dynamics

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Multilevel Color Image Segmentation using Modified Fuzzy Entropy and Cuckoo Search Algorithm

Multilevel Color Image Segmentation using Modified Fuzzy Ent...

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IEEE CIS International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Pare, Shreya Puthal, Deepak Gupta, Deepak Malik, Anand Saxena, Amit Prasad, Mukesh Univ Technol Sydney Sch Comp Sci FEIT Sydney NSW Australia Newcastle Univ Sch Comp Newcastle Upon Tyne Tyne & Wear England Natl Inst Technol Dept Comp Sci Nirjuli Arunachal Prade India Univ Delhi SSNC Coll Dept Geog Delhi India Guru Ghasidas Univ Dept Comp Sci & IT Bilaspur India

ISBN: (纸本)9781665444071

To handle the fuzziness and spatial uncertainties among pixels entailed in color images, this paper proposes a novel fuzzy entropy function for multi-threshold image segmentation based on the energy curve concept and minimum fuzzy entropy criterion. The proposed energy curve based new fuzzy entropy function (ECFE) considers intensity distribution and spatial contextual information among the pixels. To improve efficiency and threshold selection process of the method, cuckoo search algorithm is employed. For comparison, backtracking search algorithm, and Levy flight based firefly algorithm included. Comparison with recent color image multilevel segmentation techniques presented to test the effectiveness of the proposed algorithm. The performance of the proposed technique is evaluated using different satellite and natural color images. Quantitative and qualitative results demonstrate that the proposed algorithm is highly accurate, robust, and efficient for color image multilevel segmentation.

关键词： Multi-level thresholding Energy curve minimum fuzzy entropy Cuckoo search algorithm optimization algorithms

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OPTIMAL PERFORMANCE COMPARISON OF NONLINEAR ENERGY SINKS AND LINEAR TUNED MASS DAMPERS 17

OPTIMAL PERFORMANCE COMPARISON OF NONLINEAR ENERGY SINKS AND...

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作者： Yegorov (Egorov), Ivan Uden, Austin Yurchenko, Daniil North Dakota State Univ Dept Math Fargo ND 58105 USA Heriot Watt Univ Inst Mech Proc & Energy Engn Edinburgh Midlothian Scotland

ISBN: (纸本)9780791885468

This paper studies a targeted energy transfer (TET) mechanism for a two-degree-of-freedom (TDOF) model in free vibration. The model comprises a primary linear system and a secondary system in the form of an energy sink which can be non-linear. The free vibrations are considered subject to an impulsive excitation exerted on the primary system, leading to a non-zero initial velocity. The goal is to obtain the spring parameters in the nonlinear energy sink (NES) so as to maximize an energy dissipation measure (EDM) representing the percentage of impulsive energy that is absorbed and dissipated in the NES. A global optimization algorithm is used for this purpose. The optimal performance is assessed for the purely linear, linear-cubic, and purely cubic configurations of the spring connecting the primary and secondary systems. The corresponding results are compared with each other. The optimization process is performed for the EDM averaged over given ranges of the initial impulse and natural frequency in the primary system. It is shown that the type of the optimal configuration can vary depending on these ranges.

关键词： Energy transformation Energy dissipation Impulse (Physics) Dampers optimization Electrical discharge machining Free vibrations Linear systems optimization algorithms Springs Excitation

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AN EFFICIENT ALTERNATING DIRECTION METHOD FOR GRAPH LEARNING FROM SMOOTH SIGNALS

AN EFFICIENT ALTERNATING DIRECTION METHOD FOR GRAPH LEARNING...

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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Wang, Xiaolu Yao, Chaorui Lei, Haoyu So, Anthony Man-Cho Chinese Univ Hong Kong Dept Sys Engn & Engn Mgmt Hong Kong Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China

ISBN: (纸本)9781728176055

We consider the problem of identifying the graph topology from a set of smooth graph signals. A well-known approach to this problem is minimizing the Dirichlet energy accompanied with some Frobenius norm regularization. Recent works have incorporated the logarithmic barrier on the node degrees to improve the overall graph connectivity without compromising graph sparsity, which is shown to be quite effective in enhancing the quality of the learned graphs. Although a primal-dual algorithm has been proposed in the literature to solve this type of graph learning formulations, it lacks a rigorous convergence analysis and appears to have a slow empirical performance. In this paper, we cast the graph learning formulation as a nonsmooth, strictly convex optimization problem and develop an efficient alternating direction method of multipliers to solve it. We show that our algorithm converges to the global minimum with arbitrary initialization. We conduct extensive experiments on various synthetic and real-world graphs, the results of which show that our method exhibits sharp linear convergence and is substantially faster than the commonly adopted primal-dual method.

关键词： Graph Learning Graph Signal Processing ADMM optimization algorithms

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Reconfigurable reflective arrayed waveguide grating (R-RAWG) 25

Reconfigurable reflective arrayed waveguide grating (R-RAWG)

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Conference on Integrated Optics - Devices, Materials, and Technologies XXV

作者： Fernandez, Juan Felip, Joan Gargallo, Bernardo Domenech, David Dominguez, Carlos Munoz, Pascual VLC Photon SL C Camino Vera S-N Valencia 46022 Spain Univ Politecn Valencia Photon IC Grp Photon Res Labs C Camino Vera S-N Valencia 46022 Spain CSIC Inst Microelect Barcelona IMB CNM C TillersCampus Univ Autonoma Barcelona UAB Cerdanyola Del Valles 08193 Bellaterra Spain

ISBN: (纸本)9781510642140

A reconfigurable reflective arrayed waveguide grating (R-RAWG) has been designed, fabricated and tested in a silicon nitride platform. The R-RAWG has a number of advantages if compared to a traditional arrayed waveguide grating (AWG) as smaller footprint and the capability to correct to phase errors induced by fabrication defects. To implement this design, we have used tunable reflective michelson loops that produce a broadband response without the need of a modified or additional fabrication process. This approach opens the possibility to implement this design in almost any fabrication platform. By controlling the amplitude and phase of each arm, more than 12 different spectral shapes have been obtained with more than 20 dB of extinction ratio. The control is based on a new method using optimization algorithms borrowed from machine leaning developed using only the power spectrum response of one output to adapt all the variables. The reconfiguration of the band shape, the possibility to adapt the filter to the desired spectrum in one or multiple bands and the fabrication-friendly implementation for mass production make this device suitable for multiple applications as LIDAR, spectroscopy, OCT, Microwaves, Telecommunications among others.

关键词： arbitrary optical waveform generation reconfigurable integrated devices integrated photonics silicon nitride wavelength division multiplexing arrayed waveguide grating reconfigurable optical filters optimization algorithms

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Design of low power multiplierless FIR filter with enhanced adder efficiency using flower pollination optimization

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APPLIED ACOUSTICS 2021年 174卷

作者： Kumar, A. Sharma, I Balyan, L. K. PDPM Indian Inst Informat Technol Design & Mfg Ja Jabalpur Madhya Pradesh India Malaviya Natl Inst Technol Jaipur Rajasthan India

This paper presents an improved design of minimal power multiplierless finite impulse response (FIR) by using flower pollination algorithm (FPA) and newly proposed hybrid common sub-expression elimination (CSE) algorithm. The novel extract of this paper is three fold: first, enhancement of the power performance by reducing the switching activity;second, raising adder efficiency using newly proposed hybrid CSE algorithm;and third, optimizing the frequency response characteristics of filter by controlling ripples in passband and stopband region using FPA in one step. For this purpose, the minima of an objective function is achieved, constructed as sum of integral mean squared error with allowable tolerable limits to control ripples in passband and stopband region, and the dynamic power that has computed through hamming distance (HD) between two successive filter coefficients. In addition to this, the application of recently proposed CSE reduces the amount of adders, and lowers the value of HD. The significance of proposed algorithm is measured on the basis of different performance evaluation parameter such as;stopband attenuation (A(s)), stopband ripple (delta(s)), passband ripple (delta(p)), hamming distance (HD), power and amount of adders respectively. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Finite impulse response (FIR) filter Flower pollination algorithm (FPA) Dynamic power Hamming distance (HD) optimization algorithms Common sub-expression elimination algorithms (CSE)

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Explainable data-driven optimization for complex systems with non-preferential multiple outputs using belief rule base

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APPLIED SOFT COMPUTING 2021年 110卷

作者： Chang, Leilei Zhang, Limao Hangzhou Dianzi Univ Dept Automat Hangzhou Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore Singapore

To better handle problems with non-preferential multi-outputs (NPMO), a new approach is proposed in this study by employing the belief rule base (BRB) to provide a superior nonlinearity modeling ability as well as good explainability. The new approach is thus called NPMO-BRB. First, a new optimization model is constructed where the optimization objective is the integration of multi-outputs and respective constraints are designed. Then, a new optimization algorithm with a new customized gene makeup is designed where the NPMO-BRB inferencing process is embedded in the fitness calculation procedure. A practical case study on Changsha Metro Line 4 is studied to use multiple geological parameters to infer multiple operational parameters. Case study results show that NPMO-BRB has shown superior performance in comparison with the random forest (RF), the backpropagation neural network (BPNN), the Gradient Gaussian Process (GPR), as well as multiple separate BRBs. Owing to the explainability provided by the NPMO-BRB approach, further investigations into the belief distribution comparison reveal more information that can be used as practical work guidelines. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Belief rule base (BRB) Non-preferential multi-output (NPMO) optimization algorithms

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