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检索条件"主题词=artificial bee colony algorithm"

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A Discrete artificial bee colony algorithm for the Blocking Flow Shop Scheduling Problem

A Discrete Artificial Bee Colony Algorithm for the Blocking ...

引用

10th World Congress on Intelligent Control and Automation (WCICA)

作者： Deng, Guanlong Cui, Zhe Gu, Xingsheng East China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China

ISBN: (纸本)9781467313988

This paper presents a discrete bee colony algorithm for solving the blocking flow shop scheduling problem with makespan criterion. Based on the idea of iterated greedy algorithm, some new schemes for employed bee, onlooker bee and scout bee are designed. The performance of the proposed algorithm is tested on the well-known benchmark set of Taillard, and the computational results validate the effectiveness of the discrete bee colony algorithm in comparison with two recently proposed state-of-the-art algorithms. In addition, some new best known solutions for the benchmark set are provided for the considered problem.

关键词： Flow shop scheduling blocking artificial bee colony algorithm makespan

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Optimized Output Impedance for Parallel Inverters in Microgrids Utilizing ABC algorithm and Droop Control Method

Optimized Output Impedance for Parallel Inverters in Microgr...

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Global Energy Conference (GEC)

作者： Mohammed Jouda Mohammed Wadi Mohammed Salemdeeb Mehmet Rida Tur Department of Electrical and Electronics Engineering Istanbul Sabahattin Zaim University Istanbul Turkey Department of Electrical and Electronics Engineering Batman University Batman Turkey

ISBN: (数字)9798331532611

ISBN: (纸本)9798331532628

One of the highly recognized options in the efficient electrical power distribution manners of modern electrical grids involves the integration of distributed generation systems. The critical operation challenge in a microgrid is actually how to perform parallel operation for inverters that possess effective control strategies to hold stability within the system while developing appropriate power sharing. This paper describes an effective parallel inverter output impedance optimization technique based on the artificial bee colony with an advanced droop control approach. In this method, power-sharing accuracy increases considerably with the minimum range of circulating currents, thus enhancing overall stability during dynamic load transitions of the system. Extensive simulation results confirm the effectiveness of optimized droop control parameters in substantially improving stable and efficient power distribution within microgrid applications.

关键词： Simulation Microgrids Power system stability Electrical power distribution artificial bee colony algorithm Inverters Stability analysis Impedance Reliability Optimization

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Research on Optimization of Microbial Metabolic Network Model and its Application in Metabolite Synthesis

Research on Optimization of Microbial Metabolic Network Mode...

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Computer Science and Blockchain (CCSB), International Conference on

作者： Yuchen Xiang College of Life Science and Medicine Zhejiang Sci-Tech University Hangzhou Zhejiang China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

Microbial engineering has entered a new era, and the optimization of microbial metabolic network modeling and its application to metabolite synthesis has entered a new phase. Based on the EUC-GSMM concept centering on enzyme utilization constraints, it is necessary to make optimization proposals that meet the needs of metabolite synthesis in microbial engineering. Based on the dynamic evolution of the development of the microbial metabolic network model, the theoretical analysis framework of the improved ABC algorithm is constructed according to the internal logic of multi-objective optimization, and the scheduling mechanism generated by the search and update mechanism involving enzyme set function and fitness function is explained. In addition, the possibility of optimizing the microbial metabolic network model is analyzed from the parameter change and practice of EUC-GSMM. The purpose of developing EUC-GSMM is to provide a metabolite synthesis scheme that meets the expected standard for microbial engineering. We are committed to improving the quality of the program and program satisfaction. Therefore, we took a series of measures, including strengthening EUC-GSMM control based on the enzyme utilization constraint quality internal loop, constructing an interaction and feedback mechanism between the enzyme set function and enzyme utilization constraint quality perception, and establishing the EUC-GSMM and metabolite synthesis evaluation system of the program, thereby promoting the high-quality development of the field. Finally, it promotes microbial engineering, microbial metabolic network model optimization, and its application in metabolite synthesis.

关键词： Enzymes Analytical models Biological system modeling Dynamic scheduling artificial bee colony algorithm Biochemistry Logic Proposals Optimization Standards

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Hybrid Optimization algorithms for Economic and Emission Dispatch Optimization

Hybrid Optimization Algorithms for Economic and Emission Dis...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： Wei Wen Lee Mohd Ruzaini Hashim Chin Kim Gan Faculty of Electrical Technology and Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (数字)9798350382310

ISBN: (纸本)9798350382327

The artificial bee colony (ABC) algorithm is an optimization technique that uses populations and randomness. However, the standard ABC algorithm has limitations, like early convergence and easily getting stuck in local minima in some cases. Hybridizing optimization algorithms is one of the techniques for improving the algorithm’s effectiveness, adaptability, and applicability to various fields of research and application. In this paper, an optimization algorithm named bee Eel Forage algorithm (BEFA) has been proposed. BEFA algorithm is developed based on hybridizing techniques where it uses the employed bee phase and scout bee phase from the ABC algorithm and uses the resting phase from the Electric Eel Foraging Optimization (EEFO) algorithm. The efficacy of the BEFA is validated by comparing it with the ABC algorithm and the EEFO algorithm by using four mathematical benchmark functions. Moreover, the applicability of the BEFA is tested with the application of the IEEE 26 bus system to optimize the environmental and economic load dispatch problem. The results show that the BEFA algorithm outperforms the two predecessor algorithms for solving four benchmark functions and successfully minimizes the costs and emissions for the IEEE 26 bus system.

关键词： Costs Power demand Sociology Benchmark testing artificial bee colony algorithm Linear programming Statistics

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An Improved Method of artificial bee colony algorithm

An Improved Method of Artificial Bee Colony Algorithm

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2nd International Conference on Engineering Design and Optimization (ICEDO 2011)

作者： Wu, Xin-jie Hao, Duo Xu, Chao Liaoning Univ Coll Phys Shenyang 110036 Liaoning Provin Peoples R China

ISBN: (纸本)9783037852590

The basic artificial bee colony algorithm gets local extremum easily and converges slowly in optimization problems of the multi-object function. In order to enhance the global search ability of basic artificial bee colony algorithm, an improved method of artificial bee colony algorithm is proposed in this paper. The basic idea of this method is as follows: On the basis of traditional artificial bee colony algorithm, the solution vectors that found by each bee colony are recombined after each iteration, then the solution vectors of combinations are evaluated again, thus the best result is found in this iteration. In this way the possibility of sticking at local extremum is reduced. Finally the simulation experiment has been finished. The simulation experiment results have shown that the method proposed in this paper is feasible and effective, it is better than basic artificial bee colony algorithm in the global search ability.

关键词： artificial bee colony algorithm Multi-object function Optimization Local extremum

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Hybrid artificial bee colony algorithm for Solving Nonlinear System of Equations

Hybrid Artificial Bee Colony Algorithm for Solving Nonlinear...

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8th International Conference on Computational Intelligence and Security (CIS)

作者： Jia, Ruimin He, Dengxu Guangxi Univ Nationalities Coll Informat Sci & Engn Nanning 530006 Peoples R China Guangxi Univ National Coll Assoc Southeast Asian Nations Guangxi Key Lab Hybrid Computat & IC Design Anal Nanning 53006 Peoples R China

The paper presents a hybrid algorithm for solving nonlinear system of equations through combining artificial bee colony algorithm and Particle Swarm Optimization algorithm together. Numerical computations show that th... 详细信息

ISBN: (纸本)9780769548968;9781467347259

关键词： nonlinear system of equations artificial bee colony algorithm hybrid

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An artificial bee colony algorithm Based Approach to the Constrained p-Center Problem

An Artificial Bee Colony Algorithm Based Approach to the Con...

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2nd IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC)

作者： Panchumarthi, Anil Singh, Alok Univ Hyderabad Dept Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

ISBN: (纸本)9781467329255;9781467329224

p-center problem has been studied widely in operations research and computational geometry. It is a facility location problem. Here the goal is to find the best positions of p centers in a plane consisting of n demand points such that the maximum distance of any point from its nearest center is minimized. Constrained p-center problem is an extension of p-center problem where there are certain restrictions on placement of centers. This problem is more suitable to model real world applications than its unconstrained counterpart because of the practical restrictions on the placement of facilities, for example ATMs or gas stations can not be placed in the middle of a lake or a pond. This paper describes an artificial bee colony (ABC) approach for constrained p-center problem. Computational results show the effectiveness of our approach.

关键词： artificial bee colony algorithm Constrained p-Center Problem Constrained Optimization Facility Location Swarm Intelligence

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A Discrete artificial bee colony algorithm for the Traveling Salesman Problem with Time Windows

A Discrete Artificial Bee Colony Algorithm for the Traveling...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Karabulut, Korhan Tasgetiren, M. Fatih Yasar Univ Software Engn Dept Selcuk Yasar Campus Izmir Turkey Ind Engn Dept Yasar Univ Izmir Turkey

ISBN: (纸本)9781467315098

This paper presents a discrete artificial bee colony algorithm (DABC) for solving the traveling salesman problem with time windows (TSPTW) in order to minimize the total travel cost of a given tour. TSPTW is a difficult optimization problem arising in both scheduling and logistic applications. The proposed DABC algorithm basically relies on the destruction and construction phases of iterated greedy algorithm to generate neighboring food sources in a framework of ABC algorithm. In addition, it also relies on a classical 1-opt local search algorithm to further enhance the solution quality. The performance of the algorithm was tested on a benchmark set from the literature. Experimental results show that the proposed DABC algorithm is very competitive to or even better than the best performing algorithms from the literature.

关键词： traveling salesman problem with time windows artificial bee colony algorithm iterated greedy algorithm swarm intelligence heuristic optimization

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Linear Weighted Gbest-guided artificial bee colony algorithm

Linear Weighted Gbest-guided Artificial Bee Colony Algorithm

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5th International Symposium on Computational Intelligence and Design (ISCID)

作者： Zhang, Yanyu Zeng, Peng Wang, Yang Zhu, Baohui Kuang, Fangjun Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China

ISBN: (纸本)9780769548111

artificial bee colony (ABC) algorithm invented recently by Karaboga is a competitive stochastic population-based optimization algorithm. However, solution search equation used in the original ABC algorithm is good at exploration but poor at exploitation. An improved ABC algorithm called Gbest-guided ABC (GABC) was introduced by researchers to improve the exploitation of ABC algorithm. In order to improve the GABC algorithm further, we propose an improved GABC algorithm with a linear weight called WGABC, and introduce a novel solution search equation used at scout bee stage of WGABC algorithm. Experimental results tested on a set of numerical benchmark functions show that WGABC can outperform ABC and GABC algorithms in most of the experiments.

关键词： artificial bee colony algorithm Biological-inspired optimization algorithm Numerical function optimization Swarm intelligence

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An Effective artificial bee colony algorithm for Multi-objective Flexible Job-Shop Scheduling Problem

An Effective Artificial Bee Colony Algorithm for Multi-objec...

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7th International Conference on Intelligent Computing (ICIC)

作者： Zhou, Gang Wang, Ling Xu, Ye Wang, Shengyao Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol TNList Beijing 100084 Peoples R China

ISBN: (纸本)9783642259432

In this paper, an effective artificial bee colony (ABC) algorithm is proposed to solve the multi-objective flexible job-shop scheduling problem with the criteria to minimize the maximum completion time, the total workload of machines and the workload of the critical machine simultaneously. By using the effective decoding scheme, hybrid initialization strategy, crossover and mutation operators for machine assignment and operation sequence, local search based on critical path and population updating strategy, the exploration and exploitation abilities of ABC algorithm are stressed and well balanced. Simulation results based on some widely used benchmark instances and comparisons with some existing algorithms demonstrate the effectiveness of the proposed ABC algorithm.

关键词： flexible job-shop scheduling problem multi-objective optimization artificial bee colony algorithm critical path

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