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第29届中国控制与决策会议

作者： Daxing Yue Min Huang Mingqiang Yin College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern University

ISBN: (纸本)9781509046584

The design of the fourth party logistics network with stochastic demand and multi-customer behavior using the value function of prospect to despite the customer psychological behavior is studied in this *** optimization model of the fourth party logistics network design problem is established with the constraint of network investment to maximize customer *** to the characteristics of the model,the particle swarm intelligence algorithm with adaptive inertia weight is *** study is used to obtain the best combinations of algorithm and to analysis the influence of network *** results suggested that to provide the better service to customer,the certain amount of budget should be invested.

关键词： 4PL network design Stochastic demand Multi-Customer behavior pso algorithm

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Parameter optimization for a modified MEWMA control chart based on a pso algorithm

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2017年第5期46卷 4140-4153页

作者： Liu, Jian Tan, Chao Zeng, Chao Hunan Univ State Key Lab Adv Design & Mfg Vehicle Body Changsha 410082 Hunan Peoples R China

The standard multivariate exponentially weighted moving average (MEWMA) control chart with a constant smoothing parameter or diagonal matrix is based on the assumption that the samples obey standard normal distribution. With improvements in manufacturing quality and product complexity, there is always correlativity among quality characteristics, and samples will not always obey standard normal distribution. Considering the correlativity among quality characteristics, a new modified general MEWMA (GEWMA) control chart is proposed, and its performance is analyzed. Based on the Particle Swarm Optimization (pso) algorithm, a smoothing matrix optimized under certain conditions is selected and applied to a sample analysis. As a result of the parameter combination chosen by pso, the statistic function of the GEWMA control chart is better than that of the full matrix MEWMA (FEWMA) control chart.

关键词： ARL MEWMA control chart pso algorithm Smoothing matrix 62H86 62H12

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Numerical optimization and analysis on vibration characteristics of bicycles based on the novel CA-pso algorithm

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JOURNAL OF VIBROENGINEERING 2017年第6期19卷 4018-4032页

作者： Zhang, Jin Gao, Jiang Hua Wu, Jian Guo Changchun Finance Coll Dept Phys Educ Changchun 130022 Jilin Peoples R China Rizhao Polytech Student Affairs Off Rizhao 276826 Peoples R China Hunan Univ Finance & Econ Sch Math & Stat Changsha 410205 Hunan Peoples R China

Regarding the published researches on bicycles, they fail to design fatigue characteristics of the bicycle. In addition, dynamics and fatigue characteristics are not further improved by using advanced optimization algorithms. Aiming at these questions, this paper tries to optimize dynamics and fatigue characteristics of the bicycle through combining finite element model with advanced algorithms. The advanced algorithm applies ideas of cellular automation (CA) to Particle Swarm Optimization (pso), and then a hybrid CA-pso algorithm is proposed. Moreover, the finite element model is also validated by experimental test. Computational results show that: the maximum stress of bicycles is mainly distributed on the frame, especially on joints of different round pipes at different moments mainly because a dead corner is at the joint, and the dead corner can easily cause stress concentration. Under alternating forces, the stress concentration at joints will cause fatigue damage. Therefore, the service life of this position will be the shortest. As a result, the dynamics and fatigue characteristics of the joint position are taken as the optimized objective. In order to verify the optimized effectiveness of the proposed CA-pso algorithm in the paper, the widely used pso algorithm and pso-GA algorithm are also used to optimize the bicycle. When the traditional pso algorithm is used to optimize the bicycle, the root-mean-square value and maximum difference of vibration accelerations are decreased by 11.9 % and 14.3 %. When the pso-GA algorithm is used to optimize the bicycle, the root-mean-square value and maximum difference of vibration accelerations are decreased by 20.3 % and 12.9 %. When the proposed CA-pso algorithm is used to optimize the bicycle, the root-mean-square value and maximum difference of vibration accelerations are decreased by 27.1 % and 18.6 %. Compared with other two kinds of pso algorithms, optimized effects of vibration accelerations are very obvious. In a

关键词： dynamics fatigue life bicycles vibration accelerations root-mean-square value maximum difference pso algorithm pso-GA algorithm CA-pso algorithm

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Optimisation of curtain wall facades for office buildings by means of pso algorithm

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ENERGY AND BUILDINGS 2012年 45卷 189-196页

作者： Rapone, Gianluca Saro, Onorio Univ Udine Dept Elect & Mech Engn I-33100 Udine Italy

A typical curtain wall facade of an office building is modelled and studied in order to find the configuration of selected parameters that minimizes the total carbon emissions arising from building operation. Simulation based optimisation techniques, namely a pso algorithm coupled to a dynamic energy simulation engine, are used to perform a fully automated search aimed at finding the optimal values of the envelope features. The application is significant since the energy efficiency and comfort conditions of highly glazed buildings strongly depend on envelope design. Results of the optimisation are presented and discussed for four different orientations of the facade, highlighting the potential savings in comparison to a standard facade construction. The performance of the algorithm in generating satisfactory results is examined, and a way to find additional near optimal solutions to provide diversity is suggested. Finally the impact of different types of external shading devices and different climates is also investigated. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Envelope design Carbon emissions pso algorithm Curtain wall Office building

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Optimal sizing and siting of renewable energy resources in distribution systems considering time varying electrical/heating/cooling loads using pso algorithm

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INTERNATIONAL JOURNAL OF GREEN ENERGY 2018年第2期15卷 113-128页

作者： HassanzadehFard, Hamid Jalilian, Alireza Iran Univ Sci & Technol Sch Elect Engn Tehran Iran Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Sch Elect Engn Tehran Iran

Distributed Generation (DG) sources based on Renewable Energy (RE) can be the fastest growing power resources in distribution systems due to their environmental friendliness and also the limited sources of fossil fuels. In general, the optimal location and size of DG units have profoundly impacted on the system losses in a distribution network. In the present article, the Particle Swarm Optimization (pso) algorithm is employed to find the optimal location and size of DG units in a distribution system. The optimal location and size of DG units are determined on the basis of a multi-objective strategy as follows: (i) the minimization of network power losses, (ii) the minimization of the total costs of Distributed Energy Resources (DERs), (iii) the improvement of voltage stability, and (iv) the minimization of greenhouse gas emissions. The related distribution system was assumed to be composed of the fuel cells, wind turbines, photovoltaic arrays, and battery storages. The electrical, cooling, and heating loads were also considered in this article. The heating and cooling requirements of the system consist of time varying water heating load, space heating load, and space cooling load. In this study, the waste and fuel cell were used to produce the required heating and cooling loads in the distribution system. In addition, the absorption chiller was used to supply the required space cooling loads. A detailed performance analysis was carried out on 13 bus radial distribution system to demonstrate the effectiveness of the proposed methodology.

关键词： Distribution system pso algorithm renewable energy time varying loads voltage profile

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Automatic back analysis of mechanical parameters using block discrete element method and pso algorithm

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EUROPEAN JOURNAL OF ENVIRONMENTAL AND CIVIL ENGINEERING 2023年第7期27卷 2576-2586页

作者： Ma, Hang-Sheng Wang, Huan-Ling Wang, Ru-Bin Meng, Qing-Xiang Yang, Lan-Lan Hohai Univ Res Inst Geotech Engn Nanjing Peoples R China Hohai Univ Minist Educ Geomech & Embankment Engn Key Lab Nanjing Peoples R China Hohai Univ Key Lab Coastal Disaster & Def Minist Educ 1 Xikang Rd Nanjing Jiangsu Peoples R China Jiangnan Univ Sch Environm & Civil Engn Wuxi Jiangsu Peoples R China

This article presents a novel automatic pso-based back analysis method for mechanical parameters of block discrete element method. Incorporating particle swarm optimization (pso) algorithm and recursive algorithm, a parameter back-analysis program is developed. Two cases, a laboratory test of columnar jointed rock mass and a typical landslide, are implemented for validation. The results show that the proposed method is feasible and accurate. As an automatic solution for parameter back analysis, this work has broad application prospects in geotechnical engineering.

关键词： Automatic back analysis method pso algorithm discrete element method parameter back-analysis program

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New mixed-coding pso algorithm for a self-adaptive and automatic learning of Mamdani fuzzy rules

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2020年第0期89卷 103417-000页

作者： Kacimi, Mohand Akli Guenounou, Ouahib Brikh, Lamine Yahiaoui, Fateh Hadid, Nouh Univ Bejaia LTII Fac Technol Bejaia 06000 Algeria

Thanks to its algorithmic performances, pso algorithm becomes a popular tune tool for fuzzy systems in literature. However, it still encounters many complications, especially when dealing with Mamdani fuzzy system type because of its nature. The Mamdani fuzzy system is known as a linguistic model where the semantic meaning of the fuzzy rules is an intrinsic characteristic that must be retained during the learning process, while seeking for high accuracy. Therefore, to tune the Mamdani fuzzy system, it is very crucial to well represent each rule in a way that preserves this characteristic firstly, and to look for a search mechanism to optimize them throughout this topic secondly. In this paper, we introduce a new and promising approach to optimize the Mamdani fuzzy systems without a need of any prior knowledge. To the best of our knowledge, this approach is the first to optimize simultaneously the membership functions, the scaling factor parameters and the fuzzy rule conclusions with a mixed-coding pso algorithm by combining a special monitoring function and a self-adaptive threshold. The proposed approach is validated by a comparative study with other design strategies taken from Box-Jenkins gas furnace system literature and two theoretical examples in addition to a real-time control of the inverted pendulum Feedback 33-200. The obtained results proved the potential and the effectiveness of the proposed approach.

关键词： Mamdani fuzzy system pso algorithm Optimization Automatic learning Semantic interpretability

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Modelling the nonlinear relationship between CO2 emissions and economic growth using a pso algorithm-based grey Verhulst model

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JOURNAL OF CLEANER PRODUCTION 2019年 207卷 214-224页

作者： Wang, Zheng-Xin Li, Qin Zhejiang Univ Finance & Econ Sch Econ Hangzhou 310018 Zhejiang Peoples R China Zhejiang Univ Finance & Econ Ctr Reg Econ & Integrated Dev Hangzhou 310018 Zhejiang Peoples R China

A new method for discussing the relationship between CO2 emissions and economic growth is proposed using grey systems theory. GDP and CO2 emissions per capita are separately regarded as the input to, and output of, a grey system to establish a non-equigap grey Verhulst model (NE grey Verhulst model). To avoid the errors resulting from substituting a difference equation for a differential equation in grey modelling theory, the derived non-equigap grey Verhulst model (DNE grey Verhulst model) is deduced. Moreover, the structural parameters of the model are optimised using a particle swarm optimisation (pso) algorithm in an attempt to further improve modelling accuracy. Based on data relating to CO2 emissions and GDP per capita in China from 1990 to 2014, empirical research is conducted which shows that the relationship between CO2 emissions and economic growth exhibits an inverted U-shape and the emissions are in a rapid growth stage on the left of the curve. It is predicted that CO2 emissions per capita will continue to rise from 2016 to 2020 and will not reach their peak before 2030, so the Chinese government should take effective measures to reduce carbon emissions. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Grey systems theory pso algorithm Non-equigap grey Verhulst model CO2 emissions Economic growth

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Inverse boundary design radiation problem with radiative equilibrium in combustion enclosures with pso algorithm

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2015年 68卷 150-157页

作者： Payan, S. Farahmand, A. Sarvari, S. M. Hosseini Univ Sistan & Baluchestan Dept Mech Engn Zahedan 98135161 Iran Shahid Bahonar Univ Kerman Dept Mech Engn Kerman 76175133 Iran

An inverse analysis is employed to estimate the unknown heat flux distribution over the heater surface of two dimensional enclosures with regular and irregular geometries filled by non-gray participating media, from the knowledge of desired temperature and heat flux distributions over the given design surface. The medium is in radiative equilibrium. The radiative transfer equation is solved by the modified discrete ordinates method combined with two models for simulation of non-gray media. The inverse solutions are compared by using two approaches;the conjugate gradient method (CGM) and the particle swarm optimization (pso) algorithm. The pso algorithm shows accurate and reliable results in regular geometry with high optical thickness. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Non-gray media Inverse boundary design pso algorithm

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An improved pso algorithm for parameter identification of nonlinear dynamic hysteretic models

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JOURNAL OF SOUND AND VIBRATION 2017年 389卷 153-167页

作者： Zhang, Junhao Xia, Pinqi Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210016 Jiangsu Peoples R China

The nonlinear dynamic hysteretic models used in nonlinear dynamic analysis contain generally lots of model parameters which need to be identified accurately and effectively. The accuracy and effectiveness of identification depend generally on the complexity of model, number of model parameters and proximity of initial values of the parameters. The particle swarm optimization (pso) algorithm has the random searching ability and has been widely applied to the parameter identification in the nonlinear dynamic hysteretic models. However, the pso algorithm may get trapped in the local optimum and appear the premature convergence not to obtain the real optimum results. In this paper, an improved pso algorithm for identifying parameters of nonlinear dynamic hysteretic models has been presented by defining a fitness function for hysteretic model. The improved pso algorithm can enhance the global searching ability and avoid to appear the premature convergence of the conventional pso algorithm, and has been applied to identify the parameters of two nonlinear dynamic hysteretic models which are the Leishman-Beddoes (LB) dynamic stall model of rotor blade and the anelastic displacement fields (ADF) model of elastomeric damper which can be used as the lead-lag damper in rotor. The accuracy and effectiveness of the improved pso algorithm for identifying parameters of the LB model and the ADF model are validated by comparing the identified results with test results. The investigations have indicated that in order to reduce the influence of randomness caused by using the pso algorithm on the accuracy of identified parameters, it is an effective method to increase the number of repeated identifications. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Parameter identification Hysteretic model pso algorithm Rotor dynamic stall Elastomeric damper

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