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

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Study on the Workforce Scheduling and Routing Strategies of Heterogeneous Agents in Call Centers

Study on the Workforce Scheduling and Routing Strategies of ...

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2020年第五届经济与企业管理国际学术会议

作者： Mengchen Wang Xiuli Wang School of Economics and Management Nanjing University of Science and Technology

The performance of call center operations is usually associated with two factors,agent scheduling shifts and calls routing strategy,and they are dependent to some *** order to decrease the operating cost greatly,call centers need to properly allocate human resources and determine appropriate routing *** agent heterogeneity exists in the call center service system,this paper no longer assumes that agent service rates are all the *** construct an integer linear programming of the scheduling problem for call centers with agent heterogeneity,and combine the use of a discrete-event simulation model with an artificial bee colony algorithm to solve the *** evaluate the performance of the call center through discrete-event simulation experiments,and the artificial bee colony algorithm takes this performance metric as a judgment condition for satisfying the constraints,and iteratively obtains a better scheduling ***,we compare the effects of three routing strategies on the control of labor costs in enterprise *** actual data of the call center proves that considering the scheduling scheme of heterogeneous agents and the fastest server first routing can significantly reduce labor cost,and achieve effective service management.

关键词： Agent heterogeneity workforce scheduling routing strategies simulation artificial bee colony algorithm

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Unknown Parameter Estimation of a Detailed Solar PV Cell Model

Unknown Parameter Estimation of a Detailed Solar PV Cell Mod...

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IEEE Region 10 International Conference TENCON

作者： Duy C. Huynh Loc D. Ho Matthew W. Dunnigan Ho Chi Minh City University of Technology (HUTECH) Ho Chi Minh City Vietnam Heriot-Watt University Edinburgh United Kingdom

ISBN: (数字)9781728184555

ISBN: (纸本)9781728184562

This paper proposes a novel technique for unknown parameter estimation of a detailed solar photovoltaic (PV) cell model based on the artificial bee colony (ABC) algorithm and particle swarm optimization (PSO) algorithm. This combination allows to balance between the exploration and exploitation abilities of each algorithm for achieving a good optimization performance. The detailed solar PV cell model is the double-diode model with seven unknown parameters which are estimated by using the hybrid ABC-PSO algorithm. The numerical results of the parameter estimation using the hybrid ABC-PSO algorithm are compared with those using the PSO, advanced PSO and ABC algorithms showing that the convergence speed and value of the hybrid ABC-PSO algorithm are always better than the PSO, advanced PSO and ABC algorithms.

关键词： artificial bee colony algorithm Parameter estimation Numerical models Optimization Mathematical model Convergence Integrated circuit modeling

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A Hybrid Modified ABC-PSO algorithm for Optimal Robotic Path Planner

A Hybrid Modified ABC-PSO Algorithm for Optimal Robotic Path...

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International Conference on Developments in eSystems Engineering (DESE)

作者： Nadia I. Khalil Hadeel N. Abdullah Layth A. Hassnawi Communication Engineering Department University of Technology-Iraq Baghdad Iraq Electrical Engineering Department University of Technology-Iraq Baghdad Iraq Research and Development Department Ministry of Science and Technology Baghdad Iraq

Path planning is one of the most fundamental problems that must be dealt with before the mobile robot can navigate and explore autonomously in any environment. A good path-planning algorithm can save time and reduce mobile robot wear and capital investment. Path computing time and average path length are important factors over cost functions that reflect the algorithm's effectiveness, such as power consumption or average trip time. The artificial bee colony (ABC) represents one of the most important global search algorithms. The main problem with ABC is that it suffers from a slow convergence rate due to lousy exploitation and tends to get trapped in the local minima. This paper proposes and evaluates a new robot path-planning algorithm named Modified artificial bee colony (MABC). MABC algorithm design is based on modifying the ABC algorithm by cross-layer design between ABC and Particle Swarm Optimization (PSO) algorithms. The MABC is different from the original ABC algorithm in that it modifies the original one to use PSO's exploitation rather than its exploitation. On the other hand, the PSO algorithm has better exploitation but poor exploration characteristics. The evaluation and analysis were performed for several performance metrics and under different evaluation scenarios. It has been observed from the results that the MABC-PSO outperforms the original ABC with respect to average path length and convergence time which leads to improving the planning of the path.

关键词： Measurement Power demand Navigation artificial bee colony algorithm Path planning Planning Mobile robots

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Research on Prediction Method of Finish Rolling Power Consumption of Multi-Specific Strip Steel Based on Random Forest Optimization Model

Research on Prediction Method of Finish Rolling Power Consum...

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第三十九届中国控制会议

作者： XIAO Xiong DENG Daoming XIAO Yuxiong GUO Qiang ZHANG Yongjun Institute of Engineering Technology University of Science and Technology Beijing

The prediction of energy consumption data is of great importance in industrial process, among which the accurate prediction of power consumption at the production line level plays an even more essential role for energy conservation and consumption reduction under the background of steel intelligent manufacturing. In this paper, a random forest prediction model based on principal component dimensionality reduction and artificial bee colony dynamic search fusion is proposed to predict the power consumption prediction of multi-standard rolling stock in strip hot rolling finishing control section. The accurate prediction of the power consumption of the rolling section is realized with methods including data dimensionality reduction and parameter optimization. Firstly, principal component analysis is used to extract the principal components of the parameters affecting the strip rolling power consumption. Under the premise of ensuring the prediction accuracy, the computation time cost is reduced, random forest prediction model based on principal component extraction is established, and artificial bee colony is used. The dynamic search method optimizes the key parameters that affect the accuracy of random forest prediction, and further improves the prediction accuracy. The algorithm verification by using the pre-processed plant-level real-time data shows that the method can accurately predict the power loss of multi-size rolled parts with a low calculation time and a high prediction accuracy. This result indicates that the proposed model can meet the actual production of factory-level rolling demand for forecasting.

关键词： rolling power consumption principal component analysis random forest artificial bee colony algorithm multi-standard rolling

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Wind Energy and Pumped Hydro Storage Integrated Power System Risk Analysis using VaR and CVaR

Wind Energy and Pumped Hydro Storage Integrated Power System...

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International Conference on Next Generation Intelligent Systems (ICNGIS)

作者： Nitesh Kumar Singh Chaitali Koley Sadhan Gope EEE Department NIT Mizoram Aizawl India ECE Department NIT Mizoram Aizawl India EE Department Mizoram University Aizawl India

Due to the environment friendly behavior, wind energy is widely used for fulfilling the current increasing demand of electricity. With this scenario, appropriate corrective action needs to be taken; otherwise system may be in risk condition. This paper presents the analysis of economic risk of a wind power and pumped hydro storage (PHS) integrated power system. Conditional value at risk (CVaR) and value at risk (VaR) with different confidence level such as 95% and 99% are considered as risk assessment tool. Based on the MVA flow of the line obtaining from OPF solution, VaR and CVaR are calculated in this paper. Sequential quadratic programming (SQP) is used for OPF solution. The modified IEEE-30 bus system along with 24 hour load scaling factor is considered for result analysis purpose. artificial bee colony (ABC) algorithm is used to validate the results obtained from SQP approach.

关键词： Economics Reactive power Wind energy Wind power generation artificial bee colony algorithm Behavioral sciences Risk management

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Multi-objective Optimal Control of DFIG for Unbalanced Grid Voltage

Multi-objective Optimal Control of DFIG for Unbalanced Grid ...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Zan Zhang Lan Li Jinyu Zhu Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9781665434263

A multi-objective optimization control strategy based on artificial bee colony algorithm for unbalanced grid voltage doubly-fed induction generators (DFIG) is proposed to simultaneously suppress active power, reactive power double-frequency oscillations and stator current negative sequence components. The multi-objective function is established, and the multi-objective function is iteratively optimized through the artificial bee colony algorithm to obtain the optimal rotor negative-sequence current command value, and realize the multi-objective optimization control of the vector control DFIG. The simulation results verify the effectiveness of the DFIG multi-objective optimization control strategy.

关键词： Reactive power Simulation Doubly fed induction generators Rotors System integration Stators artificial bee colony algorithm

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Capacity Optimization of Battery Energy Storage Systems in a Microgrid

Capacity Optimization of Battery Energy Storage Systems in a...

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International Conference on Green Technology and Sustainable Development (GTSD)

作者： Duy C. Huynh Hieu M. Pham Loc D. Ho Hong V. Nguyen Matthew W. Dunnigan Corina Barbalata HUTECH Institute of Engineering HUTECH University Ho Chi Minh City Ho Chi Minh City Vietnam Department of Electrical Engineering HUTECH University Edinburgh United Kingdom Department of Mechanical and Industrial Engineering Louisiana State University Baton Rouge United States

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

Battery energy storage systems (BESS) play an important role in a microgrid for efficient exploration and exploitation of renewable energy sources such as solar and wind energy sources with various uncertainties. The capacity of the BESS greatly affects the operation performance of the microgrid, especially its operating costs. This paper proposes an advanced artificial bee colony (ABC) algorithm to determine the optimal capacity of BESSs to ensure minimal operating costs in the microgrid. The advanced ABC algorithm-based numerical results are compared with those using the ABC algorithm, genetic algorithm (GA), and particle swarm optimization (PSO) algorithm. The comparisons confirm the effectiveness of the proposal in the determination of the optimal capacity of the BESS in the microgrid for its operation optimization.

关键词： Renewable energy sources Costs Uncertainty Battery energy storage system Wind energy Microgrids artificial bee colony algorithm

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Telecom Big Data based Precision Marketing algorithms for Financial Industry

Telecom Big Data based Precision Marketing Algorithms for Fi...

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International Conference on Ubiquitous Computing and Communications and International Symposium on Cyberspace and Security (IUCC-CSS)

作者： Xueyi Hao Chen Cheng International School Beijing University of Posts and Telecommunications Beijing China Research Institute China United Network Communications Corporation Beijing China

ISBN: (纸本)9781665466684

The credit card business in the financial industry is an important part of the profit contribution of the bank's retail business while telecom big data, which describes the user portrait comprehensively, will help identify potential customers of credit card efficiently and accurately. This paper proposes an identification architecture for potential customers of credit card based on telecom big data and an optimized algorithm based on artificial bee colony algorithm for the adjusting parameter of eXtreme Gradient Boosting, called ABC-XGBoost, which is applied in this architecture. The experimental results proves the superiority in convergence accuracy and global searching ability of the proposed algorithm. In addition, ABC-XGBoost applied in identification for potential customers of credit card proves higher recall and precision compared with Traditional XGBoost.

关键词： Computer architecture Big Data Credit cards Boosting artificial bee colony algorithm Ubiquitous computing Telecommunications

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ABC algorithm Based System Identification Method for Three Degrees of Freedom Helicopter Model

ABC Algorithm Based System Identification Method for Three D...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Kübra Çiftçi Engin Hasan Çopur Hasan Hüseyin Bilgiç Uçak Mïhendisliği Havaculık ve Uzay Mühendisliği Uçak Mühendisliği Sivas Bilim ve Teknoloji Üniversitesi Necmettin Erbakan Üniversitesi Necmettin Erbakan Üniversitesi Sivas Konya Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

Physical laws are often taken into account when creating mathematical models of engineering systems. Simulation studies based on the created model provide guidance for real-time applications. However, discrepancies usually exist between simulation and real-time responses. Minimizing these discrepancies increases the success of the model-based studies, especially control applications. In this study, the optimization of the mathematical model was carried out with the meta-heuristic based artificial bee colony algorithm using the data obtained from the three-degree-of-freedom helicopter system. The results are promising for the utility of the proposed approach in real-time applications.

关键词： Helicopters Metaheuristics Signal processing algorithms Signal processing artificial bee colony algorithm Mathematical models Real-time systems

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ABC algorithm Based Multiuser Detector for TDRSS Forward Link MA Service

ABC Algorithm Based Multiuser Detector for TDRSS Forward Lin...

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International Conference on Computer and Communications (ICCC)

作者： Xiaoguang Chen Xu Jiang Bo Li Zhilu Wu China Academy of Space Technology Beijing China School of Electronics and Engineering Harbin Institute of Technology Harbin China China Eastern Route Corporation of South-to-North Water Diversion Beijing China

ISBN: (纸本)9781538683408

Forward link of tracking and data relay satellite system (TDRSS) can offer multiple access (MA) service for several spacecraft simultaneously by using code-division multiple-access (CDMA). This work focuses on the multiuser detection problem for TDRSS forward link MA service. An efficient heuristic method-artificial bee colony (ABC) algorithm-is employed to solve the known NP-hard problem. The discretization of ABC algorithm is explored to employ ABC algorithm in multiuser detection problem. Besides, the output of matched filter and its variations are employed as initial values for artificial bees to accelerate the convergence of ABC algorithm based multiuser detection. The simulation results show that the bit error ratio (BER) and near-far effect resistance performances of the proposed detector are quite close to the optimal multiuser detector with reasonable computational complexity. Furthermore, the proposed ABC algorithm based multiuser detector also has a large system capacity.

关键词： artificial bee colony algorithm Detectors Multiuser detection Optimization Space vehicles Matched filters Multiaccess communication

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