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multi-objective optimization of operation loop recommendation for kill web

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Journal of Systems Engineering and Electronics 2022年第4期33卷 969-985页

作者： YANG Kewei XIA Boyuan CHEN Gang YANG Zhiwei LI Minghao College of Systems Engineering National University of Defense TechnologyChangsha 410073China

In order to improve our military ’s level of intelligent accusation decision-making in future intelligent joint warfare, this paper studies operation loop recommendation methods for kill web based on the fundamental combat form of the future, i.e.,“web-based kill,” and the operation loop theory. Firstly, we pioneer the operation loop recommendation problem with operation ring quality as the objective and closed-loop time as the constraint, and construct the corresponding planning ***, considering the case where there are multiple decision objectives for the combat ring recommendation problem,we propose for the first time a multi-objective optimization algorithm, the multi-objective ant colony evolutionary algorithm based on decomposition(MOACEA/D), which integrates the multi-objective evolutionary algorithm based on decomposition(MOEA/D) with the ant colony algorithm. The MOACEA/D can converge the optimal solutions of multiple single objectives nondominated solution set for the multi-objective problem. Finally,compared with other classical multi-objective optimization algorithms, the MOACEA/D is superior to other algorithms superior in terms of the hyper volume(HV), which verifies the effectiveness of the method and greatly improves the quality and efficiency of commanders’ decision-making.

关键词： multi-objective operation loop recommendation kill web ant colony evolutionary algorithm hyper volume(HV)

multi-objective optimization of a flow straightener in a large capacity firefighting water cannon

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Journal of Hydrodynamics 2019年第1期31卷 137-144页

作者： Qing-jiang Xiang Lin Xue Kwang-Yong Kim Zhe-fu Shi National Research Centre of Pumps Jiangsu UniversityZhenjiang 212013China Department of Mechanical Engineering Inha UniversityIncheonKorea Shanghai Fire Research Institute of Ministry of Emergency Management Shanghai 200032China

In the present study,a multi-objective optimization of a flow straightener in a firefighting water cannon is performed by using the surrogate modeling and a hybrid multi-objective genetic algorithm to increase the jet range of the water *** on analysis using the three-dimensional Reynolds-averaged Navier-Stokes equations,the optimization is carried with a surrogate model and the radial basis neural *** geometric design variables,i.e.,the lengt扎 the thickness of the blade,and the radius of the outer pipe of the flow straightener,are selected for the *** pressure drop through the water can non and the area-averaged turbulent kinetic energy at the outlet of the water cannon,which are closely related to the jet range of the water cannon,are selected as the objective functions to be *** design space is determined through a parametric study,and the Latin hypercube sampling method is used to select the design points in the design *** Pareto-optimal solutions are obtained through the *** representative Pareto-optimal solutions are selected to study the trade-off between two objectives.

关键词： Firefighting water cannon multi-objective optimization surrogate model turbulence kinetic energy hydraulic loss

multi-objective Particle Swarm Optimization(MOPSO) for a Distributed Energy System Integrated with Energy Storage

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Journal of Thermal Science 2019年第6期28卷 1221-1235页

作者： ZHANG Jian CHO Heejin MAGO Pedro J. ZHANG Hongguang YANG Fubin Mechanical Engineering Department Mississippi State UniversityMississippi StateMS39762USA College of Environmental and Energy Engineering Beijing University of TechnologyBeijing 100124China

Distributed energy systems are considered as a promising technology for sustainable development and have become a popular research topic in the areas of building energy systems. This work presents a case study of optimizing an integrated distributed energy system consisting of combined heat and power(CHP), photovoltaics(PV), and electric and/or thermal energy storage for a hospital and large hotel buildings located in Texas and California. First, simulation models for all subsystems, which are developed individually, are integrated together according to a control strategy designed to satisfy both the electric and thermal energy requirements of a building. Subsequently, a multi-objective particle swarm optimization(MOPSO) is employed to obtain an optimal design of each subsystem. The objectives of the optimization are to minimize the simple payback period(PBP) and maximize the reduction of carbon dioxide emissions(RCDE). Finally, the energy performance for the selected building types and locations are analyzed after the optimization. Results indicate that the proposed optimization method could be applied to determine an optimal design of distributed energy systems, which reaches a trade-off between the economic and environmental performance for different buildings. With the presented distributed energy system, a peak shaving in electricity of about 300 kW and a reduction in boiler fuel consumption of 610 kW could be attained for the hospital building located in California for a winter day. For the summer and transition seasons, electricity peak shaving of 800 kW and 600 kW could be achieved, respectively.

关键词： multi-objective particle swarm optimization distributed energy system payback period carbon dioxide emission

multi-objective interval prediction of wind power based on conditional copula function

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Journal of Modern Power Systems and Clean Energy 2019年第4期7卷 802-812页

作者： Gang ZHANG Zhixuan LI Kaoshe ZHANG Lei ZHANG Xia HUA Yongqing WANG Institute of Water Resources and Hydro-Electric Engineering Xi’an University of TechnologyXi’an 710048China State Grid Shaanxi Baoji Electric Power Company Baoji 721000China State Grid Gansu Electric Power Company Gansu Electric Power Research InstituteLanzhou 730050China State Grid Shaanxi Electric Power Company Shaanxi Electric Power Research InstituteXi’an 710054China

Interval prediction of wind power,which features the upper and lower limits of wind power at a given confidence level,plays a significant role in accurate prediction and stability of the power grid integrated with wind ***,the conventional methods of interval prediction are commonly based on a hypothetic probability distribution function,which neglects the correlations among various variables,leading to the decrease of prediction ***,we improve the multi-objective interval prediction based on the conditional copula function,through which we can fully utilize the correlations among variables to improve prediction accuracy without an assumed probability distribution *** use the multi-objective optimization method of nondominated sorting genetic algorithm-II(NSGA-II)to obtain the optimal solution *** particular best solution is weighted by the prediction interval average width(PIAW)and prediction interval coverage probability(PICP)to pick the optimized solution in practical ***,we apply the proposed method to three wind power plants in different cities in China as examples forvalidation and obtain higher prediction accuracy compared with other methods,i.e.,relevance vector machine(RVM),artificial neural network(ANN),and particle swarm optimization kernel extreme learning machine(PSO-KELM).These results demonstrate the superiority and practicability of this method in interval prediction of wind power.

关键词： Wind power prediction Interval prediction Conditional copula function Empirical distribution function multi-objective optimization algorithm

multi-objective Optimal Dispatch for Integrated Energy Systems Based on a Device Value Tag

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CSEE Journal of Power and Energy Systems 2021年第3期7卷 632-643页

作者： Wei Tang Bangxu Wu Lu Zhang Xiaohui Zhang Jiaxin Li Liang Wang College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China

Due to the variety of devices and operating scenarios in an integrated energy system(IES),the optimal dispatch of an IES is usually *** optimal dispatch method for an IES is proposed by defining the scheduling value for each device which can be different under various ***,thinking over the private and public attributes of each operating equipment,the evaluation system is established with the actual scenarios of economic,environmental and energy-savings being ***,the economic,environmental and energy-saving benefits of each operating equipment are quantified by Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS).Therefore,the scheduling value of the device is comprehensively assessed according to the specific ***,decomposing the output of the device into direct available energy and indirect available energy,an optimal model is built with the maximum general production benefits as the objective,and is solved by MATLAB and *** simulation results show that the evaluation system can reflect multiple values of *** proposed model can unify the modeling of optimal dispatch for different scenarios in the IES and can improve dispatch efficiency,while ensuring the accuracy of the results with high computation efficiency.

关键词： Device value tag integrated energy system multi-objective optimal dispatch

multi-objective optimal design of braced frames using hybrid genetic and ant colony optimization

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Frontiers of Structural and Civil Engineering 2016年第4期10卷 472-480页

作者： Mehdi BABAEI Ebrahim SANAEI Department of Civil Engineering Faculty of Engineering University of Zanjan Zanjan 45371-38791 Iran

In this article, multi-objective optimization of braced frames is investigated using a novel hybrid algorithm. Initially, the applied evolutionary algorithms, ant colony optimization （ACO） and genetic algorithm （GA） are reviewed, followed by developing the hybrid method. A dynamic hybridization of GA and ACO is proposed as a novel hybrid method which does not appear in the literature for optimal design of steel braced frames. Not only the cross section of the beams, columns and braces are considered to be the design variables, but also the topologies of the braces are taken into account as additional design variables. The hybrid algorithm explores the whole design space for optimum solutions. Weight and maximum displacement of the structure are employed as the objective functions for multi-objective optimal design. Subsequently, using the weighted sum method （WSM）, the two objective problem are converted to a single objective optimization problem and the proposed hybrid genetic ant colony algorithm （HGAC） is developed for optimal design. Assuming different combination for weight coefficients, a trade-offbetween the two objectives are obtained in the numerical example section. To make the final decision easier for designers, related constraint is applied to obtain practical topologies. The achieved results show the capability of HGAC to find optimal topologies and sections for the elements.

关键词： multi-objective hybrid algorithm ant colony genetic algorithm displacement weighted sum method steelbraced frames

multi-objective Topology Optimization of Thermo-mechanical Compliant Mechanisms

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Chinese Journal of Mechanical Engineering 2011年第6期24卷 1123-1129页

作者： LI Dongmei ZHANG Xianmin GUAN Yisheng ZHANG Hong WANG Nianfeng School of Mechanical andAutomotive Engineering South China University of Technology Guangzhou 510640 China Guangdong Polytechnic Normal University Guangzhou 510665 China School of Computing Science University of Alberta Edmonton AB Canada

The material characteristics of a structure will change with temperature variation,and will induce stress within the ***,the optimal design for the topology of compliant mechanisms is mainly performed in single physical ***,when compliant mechanisms work in high temperature environments,their displacement outputs are generated not only by mechanical load,but also by the temperature variation which may become the prominent ***,the influence of temperature must be considered in the *** this paper,a novel optimization method for multi-objective topology of thermo-mechanical compliant mechanisms is ***,the thermal field is analyzed with finite-element method,where the thermal strain is taken into account in the constitutive relation,and the equivalent nodal thermal load is derived with the principle of virtual *** the thermal load is converted into physical loads in elastic field,and the control equation of the thermo-mechanical compliant mechanism is ***,the mathematical model of the multi-objective topology optimization is built by incorporating both the flexibility and ***,the coupling sensitivity function and the sensitivity analysis equations of thermal steady-state response are ***,optimality criteria algorithm is employed to obtain numerical solution of the multi-objective topology *** examples show that the compliant mechanisms have better performance and are more applicable if the temperature effect is taken into account in the design *** presented modeling and analysis methods provide a new idea and an effective approach to topology optimization of compliant mechanisms in electrothermic coupling field and multiphysics fields.

关键词： compliant mechanisms topology optimization thermo-mechanical coupling multi-objective coupling sensitivity

multi-objective optimization of mechanical ventilation with the aid of purifiers in two scenarios:Regular operation and mitigating the spread of respiratory infectious diseases

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Building Simulation 2023年第5期16卷 795-811页

作者： Yiqun Li Yujie Fan Chengqiang Zhi Wei Ye Xu Zhang School of Mechanical Engineering Tongji UniversityShanghai 201804China Department of Building Science Tsinghua UniversityBeijing 100084China Key Laboratory of Engineering Structure Performance Evolution and Control Ministry of EducationTongji UniversityShanghai 200092China

COVID-19 and its impact on society have raised concerns about scaling up mechanical ventilation(MV)systems and the energy *** paper attempted to combine MV and portable air cleaners(PACs)to achieve acceptable indoor air quality(IAQ)and energy reduction in two scenarios:regular operation and mitigating the spread of respiratory infectious diseases(RIDs).We proposed a multi-objective optimization method that combined the NSGA-II and TOPSIS techniques to determine the total equivalent ventilation rate of the MV-PAC system in both *** concentrations of PM_(2.5) and CO_(2) were primary indicators for *** modified Wells-Riley equation was adopted to predict RID *** open office with an MV-PAC system was used to demonstrate the method’s ***,a field study was conducted to validate the method and evaluate occupants’perceptions of the MV-PAC *** showed that optimal solutions of the combined system can be obtained based on various IAQ requirements,seasons,outdoor conditions,*** regular operation,PACs were generally prioritized to maintain IAQ while reducing energy consumption even when outdoor PM_(2.5) concentration was *** can remain constant or be reduced at low *** RID scenarios,it is possible to mitigate transmissions when the quanta were<48 h^(−1).No significant difference was found in the subjective perception of the MV and ***,the effects of infiltration on the optimal solution can be ***,our results suggested that an MV-PAC system can replace the MV system for offices for daily use and RID mitigation.

关键词： mechanical ventilation portable air cleaners infiltration multi-objective open office

multi-objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 1957-1975页

作者： Liya Yue Pei Hu Shu-Chuan Chu Jeng-Shyang Pan Fanli Business School Nanyang Institute of TechnologyNanyang473004China School of Computer and Software Nanyang Institute of TechnologyNanyang473004China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Management Chaoyang University of TechnologyTaichung413310Taiwan

Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by *** number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition *** proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum ***,we use the information gain and Fisher Score to sort the features extracted from ***,we employ a multi-objective ranking method to evaluate these features and assign different importance to *** with high rankings have a large probability of being ***,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local *** random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification *** results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER.

关键词： Speech emotion recognition filter-wrapper high-dimensional feature selection equilibrium optimizer multi-objective