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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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A dynamically adapted and weighted bat algorithm in image enhancement domain

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EVOLVING SYSTEMS 2019年第2期10卷 129-147页

作者： Dhal, Krishna Gopal Das, Sanjoy Midnapore Coll Autonomous Dept Comp Sci & Applicat Paschim Medinipur W Bengal India Univ Kalyani Dept Engn & Technol Studies Kalyani W Bengal India

This paper proposed one improved bat algorithm (BA) by incorporating one novel dynamic inertia weight and proposed self-adaptive strategies over algorithm's parameters. Chaotic sequence and developed population diversity metric are employed over BA to perform the local search and generate one improved initial population respectively. The efficacy of the proposed BA is verified by applying it to set the parameters properly of the proposed histogram equalization (HE) variant;called weighted and thresholded Bi-HE (WTBHE). The proper setting of these parameters is time consuming but crucially effects WTBHE's image enhancement ability. One novel co-occurrence matrix based objective function has been also formulated which facilitates the proposed BA for finding the optimal parameters of WBTHE which produces original brightness preserved enhanced images. Experimental results prove that the proposed BA is superior to simple BA in terms of convergence speed, robustness and maximization of objective function and WBTHE is better than some existing well-known HE variants in brightness preserving image enhancement field.

关键词： Contrast enhancement bat algorithm Dynamic inertia weight Chaotic sequence Co-occurrence matrix Population creation

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Using Binary-coded bat algorithm to Solve Hydrophobic-Polar Model Structure

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JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2015年第2期12卷 326-329页

作者： Xue, Fei Cai, Yongquan Cui, Zhihua Li, Feixiang Cao, Yang Beijing Univ Technol Coll Comp Sci & Technol Beijing 100124 Peoples R China Taiyuan Univ Sci & Technol Complex Syst & Computat Intelligence Lab Taiyuan 030024 Shanxi Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210093 Jiangsu Peoples R China

Hydrophobic-Polar model structure prediction problem is one important issue in molecular biology. This problem is to determining the native two-dimensional structure of a protein when giving the sequence of amino acid residues. Recently, a novel swarm intelligent algorithm, bat algorithm is proposed. In this paper, a new binary-coded bat algorithm is designed and applied to solve it. To show the validity of proposed algorithm, four protein sequences are employed to compare, and simulation results show it is effective.

关键词： bat algorithm Hydrophobic-Polar Model Structure Protein

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Adaptive formation-switching of a multi-robot system in an unknown occluded environment using bat algorithm

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2020年第4期4卷 465-489页

作者： Roy, Dibyendu Maitra, Madhubanti Bhattacharya, Samar TCS Res & Innovat Kolkata India Jadavpur Univ Elect Engn Dept Kolkata India

This decade has witnessed a paradigm shift in human-labor based rescue-surveillance operations. Research propositions have explored the possibility of replacing manual intervention for the management of catastrophic situations by a team of robots. However, to implement the concept into practice, the robotics community has faced several challenges. The multi-robotic system has to be duly coordinated efficaciously by controllers to automate the operations thereby saving the lives of the rescuers. Subsequently, the controller/s should be able to ensemble the robots forming a particular shape depending on the varying environmental conditions. Moreover, it would allow the group to switch its current formation so that the system could maneuver towards the target while avoiding static/dynamic obstacles. To address these challenges, we have proposed a hierarchical control strategy so that the robots could maintain a strong inter-agent cohesiveness and simultaneously could switch their formation in the face of the changing situations and could pursue the goal of arriving towards the target. The formation control law has been designed based on the echolocation principle of the bio-inspired bat algorithm. The algorithm, corroborated by the simulation results and the real-time experiments is exceptionally useful for forming the desired pattern, changing the formation adaptively whenever obstructions show up in their trajectories.

关键词： Adaptive control Formation switching bat algorithm Hierarchical control scheme

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A bat algorithm-Based Data-Driven Model for Mineral Prospectivity Mapping

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NATURAL RESOURCES RESEARCH 2020年第1期29卷 247-265页

作者： Chen, Yongliang Wu, Wei Zhao, Qingying Jilin Univ Inst Mineral Resources Prognosis Synthet Informat Changchun 130026 Jilin Peoples R China Changchun Inst Urban Planning & Design Changchun 130033 Jilin Peoples R China Jilin Univ Coll Earth Sci Changchun 130061 Jilin Peoples R China

In data-driven mineral prospectivity mapping, a statistical model is established to represent the spatial relationship between layers of metallogenic evidence and locations of known mineral deposits, and then, the former are integrated into a mineral prospectivity model using the established model. Establishment of a data-driven mineral prospectivity model can be regarded as a process of searching for the optimal integration of layers of metallogenic evidence in order to maximize the spatial relationship between mineral prospectivity and the locations of known mineral deposits. Mineral prospectivity can be simply defined as the weighted sum of layers of metallogenic evidence. Then, the optimal integration of the layers of evidence can be determined by optimizing weight coefficients of the layers of evidence to maximize the area under the curve (AUC) of the defined model. To this end, a bat algorithm-based model is proposed for data-driven mineral prospectivity mapping. In this model, the AUC of the model is used as the objective function of the bat algorithm, and the ranges of the weight coefficients of layers of evidence are used to define the search space of the bat population, and the optimal weight coefficients are then automatically determined through the iterative search process of the bat algorithm. The bat algorithm-based model was used to map mineral prospectivity in the Helong district, Jilin Province, China. Because of the high performance of the traditional logistic regression model for data-driven mineral prospectivity mapping, it was used as a benchmark model for comparison with the bat algorithm-based model. The result shows that the receiver operating characteristic (ROC) curve of the bat algorithm-based model is coincident with that of the logistic regression model in the ROC space. The AUC of the bat algorithm-based model (0.88) is slightly larger than that of the logistic regression model (0.87). The optimal threshold for extracting mineral target

关键词： bat algorithm Logistic regression Mineral prospectivity mapping Receiver operating characteristic Area under the curve Youden index

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Mobile Robot Localization Based on the Novel Leader-Based bat algorithm

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2019年第3期30卷 337-346页

作者： Neto, Wolmar A. Pinto, Milena F. Marcato, Andre L. M. da Silva, Ivo C., Jr. Fernandes, Daniel de A. Univ Fed Juiz de Fora Fac Engn BR-36036330 Juiz De Fora Brazil

This work proposes a new approach to the well-known method bat algorithm for solving the mobile robots global localization problem. The proposed method is leader-based bat algorithm (LBBA). The LBBA uses a small number of better micro-bats as leaders to influence the colony in the search for the best position, dealing satisfactorily with ambiguities during the localization process. The tests covered different scenarios aiming at comparing the proposed algorithm with other methods, such as the standard BA, the particle swarm optimization and particle filter. The results outperformed the compared methods, presenting a fast response and errors below the intended tolerance. The algorithm was tested in the robot kidnapping scenario and shows fast recovery in both simulation and in a real environment. In addition, the proposed technique showed 21% lower average error when compared with an algorithm that presents a variable quantity of particles, i.e. the adaptive Monte Carlo localization algorithm.

关键词： bat algorithm Evolutionary computation Localization algorithm Mobile robots

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An Improved bat algorithm With Time- Varying Wavelet Perturbations for Cloud Computing Resources Scheduling

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INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2023年第1期17卷 1-16页

作者： Yu, Fahong Chen, Meijia Yu, Bolin Shanwei Polytech Shanwei Peoples R China Shenzhen Inst Informat Technol Shenzhen Peoples R China

Resources scheduling is a major challenge in cloud computing because of its ability to provide many on-demand information technology services according to needs of customers. In order to acquire the best balance between speed of operation, average response time, and integrated system utilization in the resource allocation process in cloud computing, an improved bat algorithm with time-varying wavelet perturbations was proposed. The algorithm provided a perturbation strategy of time-varying Morlet wavelet with the waving property to prevent from local optimum greatly and improve the converging speed and accuracy through the guide of individual distribution to control diversity and time-varying coefficient of wavelets. The experiments showed the proposed could significantly upgrade the overall performance and the capability of resource scheduling in cloud service compared to similar algorithms.

关键词： bat algorithm Cloud Computing Morlet Wavelet Resources Scheduling Time-Varying Wavelet Wavelet

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The path planning for mobile robot based on bat algorithm

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INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL 2015年第1期9卷 50-60页

作者： Guo, Jinchao Gao, Yu Cui, Guangzhao Zhengzhou Univ Light Ind Dept Elect & Informat Engn Zhengzhou 450002 Henan Peoples R China

This article presents a novel method of global optimal path planning based on the Dijkstra algorithm and bat algorithm. This method consists of three steps: the first step is establishing the working space of mobile robot by adopting the MAKLINK graph theory, the second step is utilising the Dijkstra algorithm to obtain the sub-optimal path from the start point to the goal point, and the third step is adopting the bat algorithm to optimise the sub-optimal path so as to get the global optimal path of the robot. The result of the simulation experiment shows the proposed method is effective and can meet the real-time requirements of mobile robot. At the same time, the experiment also proves the optimal path planning of mobile robot based on bat algorithm is superior to particle swarm optimisation algorithm.

关键词： MAKLINK graph theory Dijkstra algorithm path planning bat algorithm

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A Hybrid bat algorithm for Process Planning Problem 15

A Hybrid Bat Algorithm for Process Planning Problem

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15th IFAC Symposium on Information Control Problems in Manufacturing

作者： Wang, Jinfeng Fan, Xiaoliang Zhao, Ailin Yang, Mingqiang North China Elect Power Univ Sch Energy Power & Mech Engn Baoding 071003 Peoples R China Shandong Univ Sch Informat Sci & Engn Jinan 250000 Peoples R China

In CAPP, proccss planning (PP) it-wolves two simultaneous tasks: operations selection and operations sequencing, which is difficult to be carried out to achieve the satisfied process plan. In this paper, a hybrid bat algorithm (BA) has been employed to solve PP problem. To apply BA in PP problem, a 2 x n matrix is proposed to represent the process plan solution. Some strategies of encoding, decoding, population initializing have been developed to adapt the BA algorithm to qualify to solve PP problem. To avoid local convergence, two local search strategics are incorporated into the standard BA. A modification for the local search of BA is executed to improve the bats' movement. Two new operators for the different parts of the solution representation have been proposed to diversify the bat population. A simulation experiment has been carried out to verify the validity of the hybrid BA. The interesting results show the hybrid BA can generate the satisfactory solutions. (C) 2015, IFAC (International Federation or Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Process planning bat algorithm Operations selection Operations sequencing

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Optimal sizing of stand-alone hybrid photovoltaic/wind system using bat algorithm

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INTERNATIONAL JOURNAL OF AMBIENT ENERGY 2021年第8期42卷 920-928页

作者： Marsa, Nadia Houcine, Lassad Zaafouri, Abdurrahman Chaari, Abdelkader Univ Tunisia Lab Engn Ind Syst & Renewable Energies LISIER ENSIT Tunis Tunisia Univ Tunis Natl Higher Engn Sch Tunis ENSIT Tunis Tunisia

This paper presents a new optimal sizing methodology for a stand-alone PV-wind hybrid (PWH) energy system that is serving the electricity demand for an offshore petroleum platform. A bat optimisation technique is implemented to minimise the annualised cost of the system (ACS) considering power balance constraint and to determine the optimal number of PV panels, wind turbines and batteries. The comparison of bat algorithm with Homer and particle swarm optimisation algorithm is done in this paper and it shows that bat algorithm finds optimal sizing of PWH easily with lower cost. The results show that considering reliability characteristics has a major impact on optimal sizing, load supply level and cost.

关键词： bat algorithm PSO algorithm Homer photovoltaic energy wind energy

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