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Efficient collision-free path-planning of multiple mobile robots system using efficient artificial bee colony algorithm

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ADVANCES IN ENGINEERING SOFTWARE 2015年 79卷 47-56页

作者： Liang, Jun-Hao Lee, Ching-Hung Natl Chung Hsing Univ Dept Mech Engn Taichung 402 Taiwan

This paper aims to propose a novel design approach for on-line path planning of the multiple mobile robots system with free collision. Based on the artificial bee colony (ABC) algorithm, we propose an efficient artificial bee colony (EABC) algorithm for solving the on-line path planning of multiple mobile robots by choosing the proper objective function for target, obstacles, and robots collision avoidance. The proposed EABC algorithm enhances the performance by using elite individuals for preserving good evolution, the solution sharing provides a proper direction for searching, the instant update strategy provides the newest information of solution. By the proposed approach, the next positions of each robot are designed. Thus, the mobiles robots can travel to the designed targets without collision. Finally, simulation results of illustration examples are introduced to show the effectiveness and performance of the proposed approach. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Multiple mobile robots Path planning artificial bee colony algorithm Instant update Optimization Collision avoidance

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An Effective Solution for Large Scale Single Machine Total Weighted Tardiness Problem using Lunar Cycle Inspired artificial bee colony algorithm

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020年第5期17卷 1573-1581页

作者： Sharma, Nirmala Sharma, Harish Sharma, Ajay Rajasthan Tech Univ Kota 324009 Rajasthan India Govt Engn Coll Jhalawar 326023 Rajasthan India

Single machine total weighted tardiness problem (SMTWTP) is one of the fundamental combinatorial optimization problems. The problem consists of a set of independent jobs with distinct processing times, weights, and due dates to be scheduled on a single machine. The goal of the problem is to minimize the total weighted tardiness. Several swarm intelligence (SI) motivated techniques have been proposed to solve SMTWTP. Still, the solution for large scale SMTWTP instances within a reasonable amount of time is a challenging task. artificial bee colony (ABC) algorithm is one of the efficient SI based techniques to solve real world optimization problems. This article presents an effective amended ABC based strategy to solve SMTWTP. A local search (LS) approach, influenced from the lunar cycle is proposed and hybridized with ABC to escalate the exploitation capacity of the algorithm. The proposed LS approach is titled as the lunar inspired LS (LLS) approach and the proposed hybridized strategy is known as lunar inspired ABC (LuABC) algorithm. The proposed LuABC algorithm has been applied on 25 large SMTWTP instances of job size 1000. The obtained outcomes prove that the proposed algorithm obtains the optimum solutions for all the considered instances within a reasonable amount of time.

关键词： Moon Optimization artificial bee colony algorithm Mathematical model Earth Approximation algorithms Particle swarm optimization Weighted tardiness lunar cycle optimization local search real world artificial bee colony

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An Optimal Edge Detection Using Modified artificial bee colony algorithm

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES 2016年第2期86卷 157-168页

作者： Verma, Om Prakash Agrawal, Neetu Sharma, Siddharth Delhi Technol Univ Dept Informat Technol Delhi India Ambedkar Inst Technol Dept Elect Engn Delhi India IBM India Pvt Ltd Ahmadabad Gujarat India

This paper proposes a new approach for edge detection using a combination of artificial bee colony (ABC) algorithm and an improved derivative technique. ABC algorithm simulates the foraging behavior of a honey bee swarm. The proposed approach find the edge pixels by an improved derivative technique to compute fitness function, and then applying ABC algorithm determine the most fit pixels to be considered as the edge pixels. Qualitative and quantitative analysis of the proposed approach and its comparison with other standard edge detection methods are presented. Shannon's entropy function and Pratt's figure of merit are used for quantitative analysis. The effect of variation of parameters on performance of the proposed approach is discussed. Experimental results show that proposed method outperformed most of existing techniques.

关键词： artificial bee colony algorithm Evolutionary algorithms Edge detection

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Design of the PI-UPFC-POD and PSS Damping Controllers Using an artificial bee colony algorithm

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2017年第6期28卷 762-773页

作者： Barone Martins, Luis Fabiano de Araujo, Percival Bueno Fortes, Elenilson de Vargas Macedo, Leonardo H. Parana Fed Inst Educ Sci & Technol Ave Doutor Tito S-N BR-86400000 Jacarezinho PR Brazil Sao Paulo State Univ Ave Brasil Sul 56 BR-15385000 Ilha Solteira SP Brazil Goias Fed Inst Educ Sci & Technol Rua Maria Vieira Cunha 775 BR-75804714 Jatai Go Brazil

This paper presents two variations of the artificial bee colony (ABC) algorithm, the classical and a modified version, called GBest, for the design of the proportional-integral and supplementary damping controllers: power system stabilizers and the unified power flow controller (UPFC)-power oscillation damping set. The objective is to insert additional damping to the low-frequency oscillation modes present in multimachine electrical power systems, to guarantee the small-signal stability of the system considering different loading conditions. A new current injection formulation for the UPFC is proposed and incorporated into the current sensitivity model used to represent the dynamical operation of the electric power system. Static and dynamical analysis were performed for the New England system to validate the proposed formulation and to evaluate the performance of the optimization algorithms. The results indicate that the modified version of the ABC algorithm has superior performance for this problem, providing robust solutions, that ensure the stability of the system even when small variations of the load are considered.

关键词： artificial bee colony algorithm Current sensitivity model Power oscillation damping Power system stabilizers Unified power flow controller

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A spatial exploring model for urban land ecological security based on a modified artificial bee colony algorithm

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ECOLOGICAL INFORMATICS 2019年 50卷 51-61页

作者： Wang, Haiying Qin, Fen Zhang, Xinchang Henan Univ Coll Environm & Planning JinMing St Kaifeng 475000 Peoples R China Henan Univ Key Lab Geospatial Technol Middle & Lower Yellow Minist Educ Kaifeng 475001 Peoples R China Henan Univ Res Inst Urban Big Data Kaifeng 475000 Peoples R China Henan Univ Collaborat Innovat Ctr Yellow River Civilizat Hen Kaifeng 475000 Peoples R China Sun Yat Sen Univ Sch Geog & Planning Guangzhou 510275 Guangdong Peoples R China Guangzhou Univ Sch Geog Sci Guangzhou 510275 Guangdong Peoples R China

Urban land ecological security plays an important role in alleviating human-land conflicts and in coordinating the development of natural and human resources and the environment. However, the subject of the present urban land ecological security is poorly studied. Given the circumstances, this paper presents a spatial exploring model for urban land ecological security (ULESM) based on the modified artificial bee colony algorithm (MABCA). The paper improves ABCA with a spatial grid, designed a grid-based ABCA calculation framework, ABCA's data structure, information-sharing mechanism and position selection strategy, introduces the model of spatial coupling and coordination degree for urban ecological security, and achieves spatial detection of ecologically hazardous areas. Taking Guangzhou as an example, this paper simulated the hazardous regions of the urban ecological land (assumed area: 50% of total area of Guangzhou), yielding favorable results. The results show that the ULESM based on MABCA exhibits an excellent global search and a rapid global-convergence speed, preventing a bee colony from being trapped in a local optimum. It can also effectively detect regions with urban land ecological hazards and provide intelligence-aided methods for decision making in urban ecological security and spatial planning

关键词： artificial bee colony algorithm Land ecological security Spatial coupling Spatial exploring Spatial grid Geographic information system

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Improved artificial bee colony algorithm and its Application in Classification

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JOURNAL OF ROBOTICS AND MECHATRONICS 2018年第6期30卷 921-926页

作者： Wang, Haiquan Wei, Jianhua Wen, Shengjun Yu, Hongnian Zhang, Xiguang Zhongyuan Univ Technol Zhongyuan Petersburg Aviat Coll 41 Zhongyuan Rd Zhengzhou 450007 Henan Peoples R China Zhongyuan Univ Technol Sch Elect & Informat Engn 41 Zhongyuan Rd Zhengzhou 450007 Henan Peoples R China Bournemouth Univ Fac Sci & Technol Poole BH12 5BB Dorset England

For improving the classification accuracy of the classifier, a novel classification methodology based on artificial bee colony algorithm is proposed for optimal feature and SVM parameters selection. In order to balance the ability of exploration and exploitation of traditional ABC algorithm, improvements are introduced for the generation of initial solution set and onlooker bee stage. The proposed algorithm is applied to four datasets with different attribute characteristics from UCI and efficiency of the algorithm is proved from the results.

关键词： artificial bee colony algorithm classifier SVM UCI database wrapper method

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Dynamic population artificial bee colony algorithm for multi-objective optimal power flow

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SAUDI JOURNAL OF BIOLOGICAL SCIENCES 2017年第3期24卷 703-710页

作者： Ding, Man Chen, Hanning Lin, Na Jing, Shikai Liu, Fang Liang, Xiaodan Liu, Wei Hebei Univ Technol Sch Architecture & Art Design Tianjin 300130 Peoples R China Tianjin Polytech Univ Sch Comp Sci & Software Tianjin 300387 Peoples R China Beijing Shenzhou Aerosp Software Technol Co Ltd Beijing 110000 Peoples R China Jilin Normal Univ Coll Informat & Technol Siping 136000 Peoples R China

This paper proposes a novel artificial bee colony algorithm with dynamic population (ABC-DP), which synergizes the idea of extended life-cycle evolving model to balance the exploration and exploitation tradeoff. The proposed ABC-DP is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. ABC-DP is then used for solving the optimal power flow (OPF) problem in power systems that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results, which are also compared to nondominated sorting genetic algorithm II (NSGAII) and multi-objective ABC (MOABC), are presented to illustrate the effectiveness and robustness of the proposed method. (C) 2017 The Authors. Production and hosting by Elsevier B.V.

关键词： artificial bee colony algorithm Life-cycle evolving model Optimal power flow Multi-objective optimization

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artificial bee colony algorithm based PID controller for steel stripe deviation control system

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SCIENCE PROGRESS 2022年第1期105卷 368504221075188-368504221075188页

作者： Wang, He Du, Hualong Cui, Qiuyu Song, Hua Univ Sci & Technol Liaoning Sch Mech Engn & Automat Anshan Peoples R China Univ Sci & Technol Liaoning Sch Mech Engn & Automat 189 Qianshan Middle Rd Anshan 114051 Peoples R China

To improve the performance of the PID controller for a steel strip deviation control system (SSDCS), an enhanced artificial bee colony algorithm (EABC) is proposed to optimize PID controller gains (EABC-PID). The proposed EABC changes the candidate solution equation to balance its explorative and exploitative capabilities. The experiment presents a detailed comparison of EABC-PID and four bio-inspired algorithms based PID controllers considering four types of objective functions. Simulation results show that EABC-PID proves to be superior for SSDCS compared to four bio-inspired algorithms based PID controller in terms of convergence, dynamic adjustment, and robustness.

关键词： PID controller gains optimization artificial bee colony algorithm steel strip deviation control system control method

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Design optimization of rotary regenerator using artificial bee colony algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY 2011年第A8期225卷 1088-1098页

作者： Rao, R. V. Patel, V. SV Natl Inst Technol Dept Mech Engn Surat 395007 Gujarat India

This study explores the use of artificial bee colony (ABC) algorithm for the design optimization of rotary regenerator. Maximization of regenerator effectiveness and minimization of regenerator pressure drop are considered as objective functions and are treated individually and then simultaneously for single-objective and multi-objective optimization, respectively. Seven design variables such as regenerator frontal area, matrix rotational speed, matrix rod diameter, matrix thickness, porosity, and split are considered for optimization. A case study is also presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization using ABC algorithm are validated by comparing with those obtained using genetic algorithm for the same case study. The effect of variation of ABC algorithm parameters on convergence and fitness value of the objective function has also been presented.

关键词： rotary generator design optimization artificial bee colony algorithm

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Low-Carbon Routing Based on Improved artificial bee colony algorithm for Electric Trackless Rubber-Tyred Vehicles

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Complex System Modeling and Simulation 2023年第3期3卷 169-190页

作者： Yinan Guo Yao Huang Shirong Ge Yizhe Zhang Ersong Jiang Bin Cheng Shengxiang Yang School of Mechanical Electronic and Information Engineering China University of Mining and Technology(Beijing)Beijing 100083China Inner Mongolia Research Institute China University of Mining and Technology(Beijing)Ordos 017010China Institute of Artificial Intelligence School of Computer Science and InformaticsDe Montfort UniversityLeicesterLE19BHUK.

Trackless rubber-tyerd vehicles are the core equipment for auxiliary transportation in inclined-shaft coal mines,and the rationality of their routes plays the direct impact on operation safety and energy *** studies have been done on scheduling rubber-tyerd vehicles driven by diesel oil,however,less works are for electric trackless rubber-tyred ***,energy consumption of vehicles gives no consideration on the impact of complex roadway and traffic rules on driving,especially the limited cruising ability of electric trackless rubber-tyred vehichles(TRVs).To address this issue,an energy consumption model of an electric trackless rubber-tyred vehicle is formulated,in which the effects from total mass,speed profiles,slope of roadways,and energy management mode are all *** that,a low-carbon routing model of electric trackless rubber-tyred vehicles is built to minimize the total energy consumption under the constraint of vehicle avoidance,allowable load,and endurance *** a problem-solver,an improved artificial bee colony algorithm is put *** especially,an adaptive neighborhood search is designed to guide employed bees to select appropriate operator in a specific *** order to assign onlookers to some promising food sources reasonably,their selection probability is adaptively *** a stagnant food source,a knowledge-driven initialization is developed to generate a feasible *** experimental results on four real-world instances indicate that improved artificial bee colony algorithm(IABC)outperforms other comparative algorithms and the special designs in its three phases effectively avoid premature convergence and speed up convergence.

关键词： electric trackless rubber-tyred vehicles low-carbon routing artificial bee colony algorithm

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