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Efficient line-search modified bat algorithm for solving large-scale global optimisation problems

INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2024年第4期19卷 383-393页

作者： Suhail, Enas O. Zekri, Ahmed S. El-Alem, Mahmoud M. Alexandria Univ Dept Math Fac Sci Alexandria 21526 Egypt

An efficient line-search modified bat algorithm (EMBA) is proposed to solve large-scale global optimisation problems. A balance between exploration and exploitation abilities is achieved. Firstly, a line search to an accurate step size of a particle towards the global optimum is presented. The generated step size depends on the proximity of the particle to the global optimum and it is directly proportional to the dimension of a problem. This proportion makes EMBA capable to handle the high probability of an explosion in the initial values of objective functions in large-scale optimisation problems. Secondly, the velocity of a particle is clamped within pre-defined boundaries and penalised, if necessary, to ensure that both the velocity and position of a particle are within their boundaries. These modifications combined make EMBA able to converge to the global optimum in a few iterations. The experimental results show the efficiency of EMBA when comparing with well-established algorithms.

关键词： optimisation problems global optimisation problems line-search approach large-scale problems bat algorithm meta-heuristic algorithm nature-inspired algorithm numerical results

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An Improved Spherical Vector and Truncated Mean Stabilization Based bat algorithm for UAV Path Planning

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IEEE ACCESS 2023年 11卷 2396-2409页

作者： Chen, Buqian Yang, Jin Zhang, Huizhen Yang, Meng Univ Shanghai Sci & Technol Sch Sci Shanghai Peoples R China Univ Shanghai Sci & Technol Sch Management Shanghai Peoples R China

Unmanned aerial vehicles have a wide range of applications. An intelligent optimization algorithm based on the traditional bat algorithm (BA) is investigated in this paper for UAV flight path planning in a static complex environment. The primary goal of this work is to develop a safer flight path while considering the feasibility of the UAV and the requirements for safe operation. This research proposes an improved spherical coordinate and truncated average stable strategy-based bat optimization algorithm (TMS-SBA). The algorithm uses the UAV's motion space to encode the operator, and by substituting a new bat for the worst of the old one after each iteration to increase population diversity, the algorithm can converge quickly in a complex environment while maintaining stable operation. In addition, the flight path is smoothly generated by using B-spline curves to make the planned path suitable for UAV. MATLAB simulation experiments show that, compared with other traditional swarm intelligent algorithms, TMS-SBA can successfully generate feasible and effective optimal solutions in complex environments and plan shorter, safer, and more accessible flight paths for UAV.

关键词： Unmanned aerial vehicle (UAV) path planning bat algorithm configuration space truncated mean stabilization strategy

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A new modified bat algorithm for global optimization

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RAIRO-OPERATIONS RESEARCH 2023年第5期57卷 2659-2685页

作者： Adil, Nouhaila Lakhbab, Halima Hassan II Univ Fac Sci Ain Chock Dept Math & Comp Sci Casablanca Morocco

bat algorithm, is an evolutionary computation technique based on the echolocation behaviour of microbats while looking for their prey. It is used to perform global optimization. It was developed by Xin-She Yang in 2010. Since then, it has extensively been applied in various optimization problems because of its simple structure and robust performance. Continuous, discrete, or binary, many variants were proposed over the last few years, with applications to solve real-world cases in different fields. Yet, it has one major drawback: its premature convergence due to a lack in its exploration ability. In this paper, we introduce a selection-based improvement and three other modifications to the standard version of this metaheuristic in order to enhance the diversification and intensification capabilities of the algorithm. The newly proposed method has been then tested on 20 standard benchmark functions and the CEC2005 benchmark suit. Some non-parametric statistical tests were also used to compare the New bat algorithm with other algorithms, and results indicate that the new method is very competitive and outperforms some of the state-of-the-art algorithms.

关键词： bat algorithm metaheuristics swarm intelligence roulette wheel selection

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Parameter identification of photovoltaic discrete-time equivalent model using the bat algorithm

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ENERGY REPORTS 2023年 9卷 449-458页

作者： Shen, Fu Zhang, Wei Cao, Yang Wang, Zhe Yang, Guangbing Shan, Jieshan Zhai, Suwei Kunming Univ Sci & Technol Fac Elect Power Engn Kunming 650500 Peoples R China Yunnan Power Grid Co Ltd Elect Power Inst Kunming 650217 Peoples R China

As the development of photovoltaic (PV) power generation continuously accelerated the total installed capacity of PV, the traditional static load model is difficult to meet the needs of the power grid with the increasing penetration of PV. And the dynamic model of grid-connected PV power generation is complicated and there are plenty parameters need to be identified, so the dynamic model of grid-connected PV power generation are extremely challenging to apply in wide-area power system. In this paper, a discrete-time equivalent model of PV (PDEM) is established based on the third-order dynamic differential equation of the PV power generation system and the parameters of the PDEM are identified using the least squares (LS) and the bat algorithm (BA). Besides, the dynamic characteristics of the PV power generation grid connected system with different permeability and the fitting residuals of the two methods is analyzed in the IEEE14-bus system incorporated into the PV system. The applicability of the PDEM is verified by setting short circuit grounding fault and changing the PV permeability and voltage dip. The simulation results demonstrate that the PDEM has a strong adaptability and good applicability in the case of high PV permeability with a wide application. And the applicability of the BA in identification of PDEM are given in this paper. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： PV power Dynamic equivalence bat algorithm Parameter identification

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Path Generation for a Given Performance Evaluation Value Interval by Modifying bat algorithm with Heuristic

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INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2023年第5期33卷 787-814页

作者： Wang, Fujun Cao, Zining Li, Zhen Xing, Chao Zong, Hui Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Peoples R China Minist Ind & Informat Technol Key Lab Safety Crit Software Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Collaborat Innovat Ctr Novel Software Technol & In Nanjing 211106 Peoples R China Sci & Technol Electroopt Control Lab Luoyang 471000 Peoples R China

Path generation means generating a path or a set of paths so that the generated path meets specified properties or constraints. To our knowledge, generating a path with the performance evaluation value of the path within a given value interval has received scant attention. This paper subtly formulates the path generation problem as an optimization problem by designing a reasonable fitness function, adapts the Markov decision process with reward model into a weighted digraph by eliminating multiple edges and non-goal dead nodes, constructs the path by using a priority-based indirect coding scheme, and finally modifies the bat algorithm with heuristic to solve the optimization problem. Simulation experiments were carried out for different objective functions, population size, number of nodes, and interval ranges. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm.

关键词： Path generation performance evaluation heuristic algorithm bat algorithm

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Technique for Multi-Pass Turning Optimization Based on Gaussian Quantum-Behaved bat algorithm

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1575-1602页

作者： Shutong Xie Zongbao He Xingwang Huang Computer Engineering College Jimei UniversityXiamen361021China

The multi-pass turning operation is one of the most commonly used machining methods in manufacturing *** main objective of this operation is to minimize the unit production *** paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning *** proposed algorithm mainly includes the following two *** first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population *** second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature *** performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation *** classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other ***,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining *** experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.

关键词： bat algorithm quantum behavior gaussian distribution numerical optimization multi-pass turning

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Source parameters estimation from gravity data using bat algorithm with application to geothermal and volcanic activity studies

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INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2023年第4期20卷 4167-4187页

作者： Essa, K. S. Diab, Z. E. Cairo Univ Fac Sci Dept Geophys Giza 12613 Egypt

Recently gravity data modeling plays an important role in the study of volcanic activity and geothermal investigation. Generally, gravity data modeling assumes the subsurface either homogenous or spatially variable densities within modeled source rocks and surrounding sediments. As a result, the subsurface geothermal and volcanic goals and targets are included and validated using simple-geometric sources in gravity data modeling. The bat algorithm, which is considered one of the most recently, developed metaheuristic algorithms in geophysics applications, permits to discovery and delineation of the source's parameters. Here, we presented the contribution of the bat algorithm technique in elucidating 2D gravity profiles for geothermal exploration and volcanic activity cases. The bat algorithm is based on the echo-location behavior of bats to perform global optimization. The bat optimization algorithm is applied to 2D gravity data to estimate the source's parameters such as depth, origin location, amplitude factor, and geometric shape of the causative buried body. The stability and efficiency of the introduced optimizing algorithm were checked to different synthetic cases, i.e., for model 1, which represents a horizontal cylinder model, and model 2 represents a multi-sources effect. Furthermore, the successful applications of the proposed algorithm for discovering the geothermal and volcanic activities in Japan and India were have presented. The obtained results are in good agreement with the available geological, geophysical, and borehole information.

关键词： bat algorithm Geothermal investigation Gravity anomaly Source depth Volcanic activity

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Neighborhood Search Based Improved bat algorithm for Web Service Composition

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Computer Systems Science & Engineering 2023年第5期45卷 1343-1356页

作者： Fadl Dahan Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Sciences Faculty of Computing and Information Technology AlturbahTaiz UniversityTaiz9674Yemen

Web services are provided as reusable software components in the services-oriented *** complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service(QoS)*** workflow consists of tasks where many services can be considered for each *** for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial(NP)-hard *** work focuses on the Web Service Composition(WSC)problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the *** proposed algorithm determines the optimal combination of the web services to satisfy the complex user *** also addresses the bat algorithm(BA)shortcomings,such as the tradeoff among exploration and exploitation searching mechanisms,local optima,and convergence *** proposed enhancement includes a developed cooperative and adaptive population initialization *** elitist mechanism is utilized to address the BA convergence *** tradeoff between exploration and exploitation is handled through a neighborhood search *** benchmark datasets are selected to evaluate the proposed bat algorithm’s *** simulation results are estimated using the average fitness value,the standard deviation of the fitness value,and an average of the execution time and compared with four bat-inspired *** is observed from the simulation results that introduced enhancement obtains significant results.

关键词： Cloud computing web service composition bat algorithm serviceoriented architecture

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Six Phase Transmission Line Protection Using bat algorithm Tuned Stacked Sparse Autoencoder

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2023年第2期51卷 113-130页

作者： Rao Althi, Tirupathi Koley, Ebha Ghosh, Subhojit Shukla, Sunil Kumar Natl Inst Technol Raipur Elect Engn Dept Raipur India Nirma Univ Inst Technol Dept Elect Engn Ahmadabad India MITS Gwalior Dept Informat Technol Gwalior India

Six-phase transmission lines have the capability to address the continually evolving power demand. It allows upgrading the power transfer capability of the prevailing three-phase double circuit line without major changes in the transmission corridors. However, the operational performance of any six-phase system is highly dependent on its protection scheme. The possibility of larger number of faults in six-phase system complicates the protection task. Furthermore, the harmonics intrusion arising because of nonlinear loading compromises the reliability of the conventional threshold-based protection schemes. In this regard, this article addresses the above-mentioned challenges by developing a protection scheme based on the hybrid frameworks of bat algorithm and stacked sparse autoencoder-deep neural network (SAE-DNN). To overcome the limitation of SAE-DNN regarding optimal selection of architecture and tuning parameters, the selection task has been formulated as an optimization problem and solved using bat algorithm. The use of raw voltage and current signals as input to the SAE-DNN reduces the overall complexity of the protection scheme. The efficacy of the proposed scheme has been validated for all 120 types of faults under varying operating, loading and fault scenarios. Furthermore, the proposed scheme has been validated for practical settings by performing real-time simulations on OPAL-RT digital simulator.

关键词： bat algorithm deep neural network six phase transmission line protection stacked sparse autoencoder real time validation

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Experimental Validation of LQR Weight Optimization Using bat algorithm Applied to Vibration Control of Vehicle Suspension System

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IETE JOURNAL OF RESEARCH 2023年第11期69卷 8142-8152页

作者： Yuvapriya, T. Lakshmi, P. Elumalai, Vinodh Kumar Anna Univ Dept EEE Coll Engn Chennai 600025 Tamil Nadu India Vellore Inst Technol Sch Elect Engn Vellore 632014 Tamil Nadu India

To deal with multiple constraints of vehicle active suspension system (ASS) including road handling and passenger safety, this paper presents an optimal linear quadratic regulator (LQR) approach which employs bat algorithm (BA) for selection of optimal state and input penalty matrices of LQR. We formulate the conflicting control objectives of ASS, namely, ride comfort and passenger safety as a multi-constraint optimization problem and employ the BA for weight selection of LQR. The key advantage of the proposed approach is that the local optima problem is avoided by utilizing the frequency tuning and random walk technique in BA. The performance of the proposed approach is experimentally tested using hardware in loop (HIL) testing on a quarter car ASS for realistic road profiles. Moreover, the performance is benchmarked against grey wolf optimization tuned LQR. Experimental results assessed based on ISO 2631 standards highlight the significant improvement in the ride comfort and passenger safety.

关键词： Active suspension system LQR bat algorithm HIL testing disturbance rejection

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