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The 4th Annual 2018 International Conference on Management Science and Engineering(MSE 2018)

作者： Chunyan Qiu Xi Yang Yang Liu School of Management Science and Information Engineering Jilin University of Finance and Economics Key Laboratory of Logistics Industry Economy and Intelligent Logistics Jilin University of Finance and Economics

The use of intelligent optimization algorithms to optimize vehicle routing problem has become a hot topic in international *** normal particle swarm optimization(PSO) algorithm is a validated evolutionary computation way of searching the extreme of function,which is simple in application and quick in convergence,but low in precision and easy in premature *** this paper,the improved particle swarm optimization algorithm is used to optimize the logistics vehicle path by setting the inertia factor to *** the simulation experiment analysis,the improved particle swarm optimization algorithm has better convergence(linear convergence).This algorithm avoids the problem that the global optimal is replaced by the local value,reduces the number of iterations required for search in optimal solution,and shortens the optimization time.

关键词： Vehicle Routing Optimization particle swarm algorithm

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CONTROLLER DESIGN FOR ROTARY INVERTED PENDULUM SYSTEM USING particle swarm OPTIMIZATION algorithm

CONTROLLER DESIGN FOR ROTARY INVERTED PENDULUM SYSTEM USING ...

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IEEE Canadian Conference on Electrical and Computer Engineering

作者： Afshin Rahimi Kaamran Raahemifar Krishna Kumar Hekmat Alighanbari Ryerson University Toronto Ontario Canada

ISBN: (纸本)9781479900312

This paper presents particle swarm optimization approach for designing Rotary Inverted Pendulum (RIP) controller. The goal is to balance the pendulum in the inverted position. The intuition of this work is using state-feedback controller as the stabilizer component of the system whereas in other existing systems, only Proportional-Integral-Derivative (PID) is used for that purpose. Simulation results demonstrate effectiveness of the proposed controller design method and can be considered as promising ways for control of various similar nonlinear systems.

关键词： Optimization Control RIP PSO State-Feedback parametric subharmonic oscillator Controllers State feedback INVERTED PENDULUM controller design Standing Orders ripping particle swarm algorithm particle swarm optimization algorithms Clock weights

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Study on Train Operation Adjustment Based on Collaborative particle swarm algorithms 2nd

Study on Train Operation Adjustment Based on Collaborative P...

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International Conference on Electrical and Information Technologies for Rail Transportation - Electrical Traction

作者： An, Yazheng Qin, Yong Meng, Xuelei Wang, Ziyang Beijing Jiaotong Univ Beijing Res Ctr Urban Traff Informat Sensing & Se Beijing 100044 Peoples R China Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China

ISBN: (纸本)9783662493700;9783662493687

The paper establishes the operation adjustment model in accordance with constraints of the train operation based on the characteristic of high real-time and dynamic and the fitness function aiming at getting the least level of delay time and the number of delay times. In order to solve the established operation adjustment model, the method of cooperation is introduced to improve the typical particle swarm algorithm, which improves the efficiency of operation and the global optimum. Finally, taking the train operation adjustment of dedicated passenger line between Beijing and Shenyang as an example, the model and algorithm are verified. It can be seen that the method is efficient and feasible and it has a good guiding significance for train operation adjustment.

关键词： Operation adjustment Delay times Cooperation particle swarm algorithm

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An optimization of 15.12 GHz SPDT switch using particle swarm optimization algorithm

An optimization of 15.12 GHz SPDT switch using particle swar...

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4th International Conference on Intelligent and Advanced Systems (ICIAS) and A Conference of World Engineering, Science and Technology Congress (ESTCON)

作者： Lau, T. L. Neoh, S. C. Marzuki, A. Univ Malaysia Perlis Sch Microelect Engn Perlis Malaysia Univ Sains Malaysia Sch Elect & Elect Engn George Town Malaysia

ISBN: (纸本)9781457719677

In this paper, a simulation-based particle swarm optimization (PSO) approach is developed to optimize the operational parameters of a 15.12 GHz single pole double throw (SPDT) switch. The Agilent Advance Design System (ADS) is used to synthesize the performance of the switch design while PSO is employed as the optimizer for achieving the required switch performance. The performance of the designed SPDT switch is assessed in terms of insertion loss and isolation. Simulation results show that the proposed component values of SPDT switch is manage to fulfill the required specifications, achieving 25.978dB of isolation loss and 3.077dB of insertion loss.

关键词： single pole double throw switch insertion loss single-pole double-throw (SPDT) particle swarm algorithm particle swarm optimization switching characteristics

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Seismic design of water distribution networks using auto-generation techniques

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STRUCTURE AND INFRASTRUCTURE ENGINEERING 2017年第7期13卷 831-843页

作者： Liu, Wei Xu, Liang Li, Jie Tongji Univ State Key Lab Disaster Reduct Civil Engn Shanghai Peoples R China Tongji Univ Dept Struct Engn Shanghai Peoples R China Shanghai Nucl Engn Res & Design Inst Shanghai Peoples R China

A feasible approach that uses an auto-generation technique is proposed to design and retrofit water distribution networks (WDNs) subjected to earthquakes. Because pipelines are laid along roads, the road information is extracted and then integrated into the auto-generation technique whereby the rules relevant to laying the pipelines are established. An optimisation model with parameters of network topology and pipeline diameter is developed to design and retrofit WDNs, whose seismic functional reliability index serves as a constraint. An intelligent optimisation program via a particle swarm algorithm is employed to generate the optimal network after a number of evaluations and evolutions. For illustrative purposes, a hypothetical and a real WDN model are investigated, respectively. Numerical results indicate that the optimisation and design method developed in this paper provides a new perspective towards the rational balance between risk and investment.

关键词： Water distribution networks network topology seismic optimisation design particle swarm algorithm auto-generation technique

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Measurement of absolute displacement based on dual-path submicron-aperture fiber point-diffraction interferometer

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OPTIK 2017年 140卷 802-811页

作者： Wang, Zhichao Wang, Daodang Gong, Zhidong Xu, Ping Liang, Rongguang Zhao, Jufeng Li, Wei China Jiliang Univ Coll Metrol & Measurement Engn Hangzhou 310018 Zhejiang Peoples R China Univ Arizona Coll Opt Sci Tucson AZ 85721 USA Hangzhou Dianzi Univ Inst Elect & Informat Hangzhou 310018 Zhejiang Peoples R China

The measurement of three-dimensional absolute displacement within large range can be achieved with submicron-aperture fiber point-diffraction interferometer (SFPDI), in which the numerical iterative algorithm for displacement reconstruction and point-diffraction wavefront determine the achievable measurement accuracy, reliability and efficiency of the system. To avoid the poor measurement accuracy in the lateral direction parallel to the fringe direction in the SFPDI with only one fiber pair, a dual-path SFPDI (DP-SFPDI) based on modified fast searching particle swarm optimization (PSO) algorithm is proposed to realize the rapid and accurate measurement of three-dimensional absolute displacement. Based on the DP-SFPDI with two submicron-aperture fiber pairs and modified PSO method, the measurement reliability, efficiency and accuracy in all the three dimensions of the system are significantly improved, making it more feasible for practical application. The effect of point-diffraction wavefront error on the measurement is analyzed. Both the numerical simulation and comparison experiments have been carried out to demonstrate the accuracy and feasibility of the proposed DP-SFPDI system, high measurement accuracy, convergence rate and efficiency have been realized with the proposed method. (C) 2017 Published by Elsevier GmbH.

关键词： Absolute displacement measurement Dual-path point-diffraction interferometer Wavefront error particle swarm algorithm

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Optimizing dam and reservoirs operation based model utilizing shark algorithm approach

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KNOWLEDGE-BASED SYSTEMS 2017年 122卷 26-38页

作者： Ehteram, Mohammed Karami, Hojat Mousavi, Sayed-Farhad El-Shafie, Ahmed Amini, Zahra Semnan Univ Fac Civil Engn Dept Water Engn & Hydraul Struct Semnan Iran Univ Malaya Fac Engn Dept Civil Engn Kuala Lumpur Malaysia Univ Technol Malaysia Fac Engn Dept Civil Engn Kuala Lumpur Malaysia

Computational intelligence (CI) is a fast evolving area in which many novel algorithms, stemmed from various inspiring sources, were developed during the past decade. Nevertheless, many of them are dispersed in different research directions, and their true potential is thus not fully utilized yet. Therefore, there is a need to investigate the potential of these methods in different engineering optimization problems. In fact, shark algorithm is a stochastic search optimization algorithm which is started first in a set of random generated potential solutions, and then performs the search for the optimum one interactively. Such procedure is appropriate to the system features of the reservoir system as it is a stochastic system in nature. In this article, investigation of the potential of shark algorithm is examined as an optimization algorithm for reservoir operation. To achieve that real single reservoir and multi-reservoir optimal operations have been performed utilizing shark algorithm. Many performances indexes have been measured for each case study utilizing the proposed shark algorithm and another existing optimization algorithms namely, Genetic algorithm (GA) and particle swarm Optimization (PSO). The results showed that the proposed shark algorithm outperformed the other algorithms and achieved higher reliability index and lesser vulnerability index. Moreover, standard deviation and coefficient of variation in Shark algorithm were less than the other two algorithms, which indicates its superiority. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Shark algorithm Multiple-reservoir systems Genetic algorithm particle swarm algorithm

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Wind Farm Layout Design Using Cuckoo Search algorithms

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Applied Artificial Intelligence 2018年第9-10期32卷 956页

作者： Rehman, S Ali, S S Khan, S A Research Institute King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Center of Intelligent Signal & Imaging Research Universiti Teknologi PETRONAS Bandar Seri Iskandar Tronoh Malaysia Computer Science Department University of Pretoria Pretoria South Africa

Wind energy has emerged as a strong alternative to fossil fuels for power generation. To generate this energy, wind turbines are placed in a wind farm. The extraction of maximum energy from these wind farms requires optimal placement of wind turbines. Due to complex nature of micrositing of wind turbines, the wind farm layout design problem is considered a complex optimization problem. In the recent past, various techniques and algorithms have been developed for optimization of energy output from wind farms. The present study proposes an optimization approach based on the cuckoo search (CS) algorithm, which is relatively a recent technique. A variant of CS is also proposed that incorporates a heuristic-based seed solution for better performance. The proposed CS algorithms are compared with genetic and particle swarm optimization algorithms which have been extensively applied to wind farm layout design. Empirical results indicate that the proposed CS algorithms outperformed the genetic and particle swarm optimization algorithms for the given test scenarios in terms of yearly power output and efficiency.

关键词： Wind Energy Conversion Systems Wind algorithms maximum energy SEARCHING algorithm Energy output Wind farms particle swarm algorithm layout design Cuculidae Fossil Fuels

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Optimization of carbon emission considering production planning at enterprise level

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JOURNAL OF CLEANER PRODUCTION 2017年 162卷 635-645页

作者： Su, Qiang Yang, Wei Liu, Yaowu Tongji Univ Sch Econ & Management Shanghai Peoples R China China Aeronaut Radio Elect Res Inst Shanghai Peoples R China

Greenhouse gas (GHG) emissions cause climate changes, and their impact on the environment continues to increase. As a result, there is an urgent need to accelerate efforts to reduce GHG emissions. In industry, the majority of the current methods of reducing GHG emissions depend on technical enhancements of the facility and equipment. These methods focus on local optimization for carbon emission reduction in enterprises and may require additional time, money and effort for satisfactory implementation. Unlike technical approaches that focus on the equipment, this paper proposes an approach that combines carbon footprint analysis and production planning. The carbon footprint of the entire company's operational process can be analyzed systematically using this approach. Subsequently, carbon emissions can be reduced significantly through production planning and optimization. To test the effectiveness of the proposed approach, a pharmaceutical enterprise is employed as an example. A production planning model is constructed based on the energy consumption analysis of different units and equipment. Using this model, the carbon emissions of the enterprise can be analyzed, and the corresponding production plan can be developed. To determine the optimal solution, a hybrid discrete particle swarm algorithm is developed and tested based on real data collected from the pharmaceutical enterprise. The experimental results demonstrate that the proposed novel approach is effective and carbon emissions of the enterprise can be reduced by an average of 6.77%, or a reduction in CO2 emissions of 610.2 tons per year. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Cleaner production Carbon emissions Energy consumption Production planning particle swarm algorithm

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RCS reduction for grazing incidence based on coding metasurface

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ELECTRONICS LETTERS 2017年第20期53卷 1381-1382页

作者： Zhou, Yulong Cao, Xiang-yu Gao, Jun Li, Sijia Liu, Xiao Air Force Engn Univ Sch Informat & Nav 1 Feng Hao Rd Xian 710077 Shaanxi Peoples R China

A coding metasurface is proposed for reducing radar cross section (RCS) under grazing incidence. Two elements with different reflection phases are selected for the metasurface, and 7 x 7 artificial magnetic conductor unit cells are utilised to construct a metamaterial block. Then the arrangement of blocks is optimised by particle swarm algorithm (PSA). The phase difference between two elements contributes to RCS reduction under grazing incidence. The obtained results demonstrate that a wideband RCS reduction is achieved by the coding metasurface ranging from 6 to 13 GHz. In addition, the monostatic RCS reduction is also achieved under a grazing incidence. For x-polarised incidence, the monostatic RCS reduction is >6 dB from 77 degrees to 90 degrees. For y-polarised incidence, the monostatic RCS reduction is >6 dB from 69 degrees to 80 degrees, and the maximum reduction is 17.5 dB under the 75 degrees incident angle.

关键词： radar cross-sections encoding frequency selective surfaces microwave metamaterials particle swarm optimisation grazing incidence coding metasurface wideband radar cross section reduction artificial magnetic conductor unit cell metamaterial block particle swarm algorithm PSA wideband RCS reduction x-polarised incidence monostatic RCS reduction y-polarised incidence frequency 6 GHz to 13 GHz gain 17 5 dB

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