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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Guo, Xinrong Mei, Fang Sun, Geng Zheng, Tingting Jilin Univ Coll Software Changchun 130012 Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Univ Waterloo Coll Elect & Comp Engn Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781665491228

With the rapid development of wireless communication, unmanned aerial vehicle (UAV) networks have received extensive attention and been applied in many fields, but some challenges exist in their applications, such as the issue of security when implementing communication. In this paper, a virtual antenna array (VAA) is formed in multiple UAV units using collaborative beamforming (CB) technology. Under the interference of multiple eavesdroppers, secure communication with the ground base station (BS) is achieved. To achieve better performance, we formulate a multi-objective optimization problem for UAV network security communication (SCMOP), and jointly optimize the positions and excitation current weights of UAVs to set the null values in the direction of known eavesdroppers, reduce the sidelobe levels (SLLs) and enhance the directivity of the main lobe (ML). Since the formulated SCMOP is an NP-hard problem, we propose an improved the third non-dominated sorting genetic algorithm (IMNSGA-III) with chaos operator and crossover and mutation operators to solve the problem in this paper. The simulation results show that the IMNSGA-III can solve the SCMOP well and obtain the best results compared with other benchmark algorithms.

关键词： UAV networks collaborative beamforming secure communication multi-objective optimization problem evolutionary algorithms

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Revenue optimization modeling for renewable energy resource mix for sustainable development

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JOURNAL OF REVENUE AND PRICING MANAGEMENT 2021年第2期20卷 108-115页

作者： Gupta, Neha Agarwal, Mohini Garg, Pratibha Bansal, Manoj Amity Univ Uttar Pradesh Amity Sch Business Noida India

The adoption and attainment of sustainable development goals have diverted developing nations like India towards the use of renewable resource for meeting the growing need for electricity. With the advancement in technology for generating electricity, the concern is to develop such renewable energy mix that can help satisfy the electricity demand and be environment friendly. In this paper, one such problem wherein the three conflicting criterion such as maximization of energy savings, maximization of efficiency and minimization of the cost of installation has been considered for designing a multi-objective optimization model to meet the growing demand of electricity. Interactive fuzzy goal programming technique with three different functional forms of membership function namely linear, exponential, and hyperbolic have been used to solve the proposed problem. The results have shown substantial adequacy in meeting the desired load demand and at the same time reduction in installation cost has been seen which in turn will impact the revenue generation.

关键词： Energy efficiency Interactive fuzzy goal programming technique multi-objective optimization problem Renewable sources Revenue optimization

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optimization Spectrum Decision Parameters in CR using Autonomously Search Algorithm 13

Optimization Spectrum Decision Parameters in CR using Autono...

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13th IEEE International Conference on Signal Processing (ICSP)

作者： Li, Yongcheng Shen, Hai Wang, Manxi State Key Lab Complex Electromagnet Environm Effe Luoyang Peoples R China Shenyang Normal Univ Coll Phys Sci & Technol Shenyang Liaoning Peoples R China Shenyang Inst Automat Control Theory & Control Engn Postdoctoral Res St Shenyang Liaoning Peoples R China

ISBN: (纸本)9781509013456

In order to solve the contradiction between wireless communication service demand and spectrum resource shortage and enhance the utilization rate of spectrum, Cognitive Radio technology is necessary. Firstly, this paper presents a cognitive engine framework structure, and then the concept of bio- inspired and its application in CR computing were emphatically introduced. Finally, in order to solve spectrum parameters problem, this paper proposed based on autonomously search algorithm. Based on population evolution, ASA algorithm employs the foraging, reproduction, selection and mutation operators, and was tested under the multicarrier simulation environment. The experiment results show that ASA algorithm can better adjust each subcarrier communication parameters according to the requirement of cognitive engine parameters optimization, which include transmitted power, modulation mode, and bit-error-rate and so on, and finally satisfy the channel condition and the dynamic changes of the user service.

关键词： Cognitive Engine Bio-inspired Computing Cognitive Radio Automously Search Algorithm multi-objective optimization problem

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3D Path Planning of the Solar Powered UAV in the Urban-Mountainous Environment with multi-objective and multi-Constraint Based on the Enhanced Sparrow Search Algorithm Incorporating the Levy Flight Strategy

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Guidance, Navigation and Control 2024年第1期4卷 149-175页

作者： Pengyang Xie Ben Ma Bingbing Wang Jian Chen Gang Xiao College of Engineering China Agricultural UniversityBeijing 100083P.R.China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310027P.R.China Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province College of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhou 310058P.R.China Key Laboratory of Smart Agricultural Technology(Yangtze River Delta) Ministry of Agriculture and Rural AffairsNanjing 210044P.R.China Key Laboratory of Smart Agricultural Technology in Tropical South China Ministry of Agriculture and Rural AffairsGuangzhou 510642P.R.China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191P.R.China

In response to practical application challenges in utilizing solar-powered unmanned aerial vehicle(UAV)for remote sensing,this study presents a three-dimensional path planning method tailored for urban-mountainous *** into account constraints related to the solar-powered UAV,terrain,and mission objectives,a multi-objective trajectory optimization model is transferred into a single-objective optimization problem with weight factors and multiconstraint and is developed with a focus on three key indicators:minimizing trajectory length,maximizing energy flow efficiency,and minimizing regional risk ***,an enhanced sparrow search algorithm incorporating the Levy flight strategy(SSA-Levy)is introduced to address trajectory planning challenges in such complex *** simulation,the proposed algorithm is compared with particle swarm optimization(PSO)and the regular sparrow search algorithm(SSA)across 17 standard test functions and a simplified simulation of urban-mountainous *** results of the simulation demonstrate the superior effectiveness of the designed improved SSA based on the Levy flight strategy for solving the established single-objective trajectory optimization model.

关键词： Solar powered UAV multi-objective optimization problem single-objective optimization problem multi-constraint sparrow search algorithm Levy flight strategy

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Ranking of Wireless Access Networks for Providing QoS in Heterogeneous Environment

Ranking of Wireless Access Networks for Providing QoS in Het...

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8th ACM International Symposium on Mobility Management and Wireless Access

作者： Karam, Fazal Wahab Jensen, Terje Norwegian Univ Sci & Technol Ctr Quantifiable Qual Serv N-7034 Trondheim Norway

ISBN: (纸本)9781450302777

How to select a proper access network for providing Quality of Service (QoS) in a heterogeneous environment is a unsolved question. This paper introduces a novel ranking algorithm to evaluate the QoS in heterogeneous networks by posing the problem as a multi-objective optimization problem. We focus on a multi-provider environment, including issues like administration domain, access technology, terminal, and application.

关键词： Heterogeneous networks ranking algorithm QoS multi-objective optimization problem

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multi-objective multiclass support vector machine for pattern recognition

Multi-objective multiclass support vector machine for patter...

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Annual Conference on the Society-of-Instrument-and-Control-Engineers

作者： Tatsumi, K. Hayashida, K. Higashi, H. Tanino, T. Osaka Univ Grad Sch Engn Dept Elect Elect & Informat Engn Osaka Japan

ISBN: (纸本)9784907764289

Support vector machines were originally proposed for the binary classification. For multiclass classification, some kinds of extensions of SVMs have been proposed. In this paper, we focus on "all together" method, where an extended SVM is constructed by using a piece-wise linear function. This model is formulated as an optimization problem which maximizes margins between each pair of classes for the generalization ability. However, as we point out in this paper, the model does not correctly represent the margins. Therefore, we propose a multi-objective model which exactly maximizes all margins. In addition, we derive a new SVM as a single-objective quadratic programming problem and apply the proposed SVM to some problems and verify its efficiency.

关键词： multiclass classification support vector machine maximization of margins multi-objective optimization problem

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multi-objective optimization of Particle Reinforced Silicone Rubber Mould Material for Soft Tooling Process

Multi-Objective Optimization of Particle Reinforced Silicone...

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8th International Conference of Simulated Evolution and Learning

作者： Nandi, Arup Kumar Datta, Shubhabrata CSIR Cent Mech Engn Res Inst Durgapur 713209 WB India Birla Inst Technol Deoghar Campus Jasidih Jharkhand 814142 India

ISBN: (纸本)9783642172977

multi-objective optimizations of various conflicting objectives in designing particle reinforced silicone rubber are conducted using evolutionary algorithms to reduce the processing time of soft tooling process. A well-established evolutionary algorithm based multi-objective optimization tool, NSGA-II is adopted to find the optimal values of design parameters. From the obtained Pareto-optimal fronts, suitable multi-criterion decision making techniques are used to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of soft tooling process for industrial applications.

关键词： multi-objective optimization problem evolutionary algorithm particle reinforced flexible mould material soft tooling cooling time

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Investigating Communications Energy Efficiency Tradeoff Between UAV Users and Small-cell Users 32

Investigating Communications Energy Efficiency Tradeoff Betw...

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32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE PIMRC)

作者： Hashemi, Ramin Mili, Mohammad Robat Ali, Samad Beyranvand, Hamzeh Latva-aho, Matti Univ Oulu CWC Oulu Finland Islamic Azad Univ Tehran Iran Amirkabir Univ Technol Tehran Polytech Dept Elect Engn Tehran Iran

ISBN: (纸本)9781728175867

In this paper, a novel method is proposed to study the tradeoff between energy efficiency (EE) of small-cell users and unmanned aerial vehicles (UAV) users in multi-cell orthogonal frequency division multiple access (OFDMA)-based networks. Contrary to the prior works that only maximize the EE of the UAV network subject to some constraints on transmit power of UAV users, we formulate a multi-objective optimization problem (MOOP) that jointly maximize the EE of small-cell and UAV users while guaranteeing the minimum rate for UAV users as well as maximum transmit powers for the corresponding small-cell and UAV BSs. The proposed MOOP is transformed into a single optimization problem (SOOP) by the weighted Tchebycheff approach. Then, an iterative technique is used to optimize alternatively subchannels and transmission powers of small-cell and UAV networks at each step. Numerical results show that a substantial performance gain can be obtained over the existing solutions.

关键词： Energy efficiency heterogeneous network multi-objective optimization problem OFDMA small-cell unmanned aerial vehicles

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Modeling Green-aware Job Scheduling problem in Decentralized Data Centers 5

Modeling Green-aware Job Scheduling Problem in Decentralized...

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5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Minh, Ha Tuan Samejima, Masaki Osaka Univ Grad Sch Informat Sci & Technol 1-5 Yamadaoka Suita Osaka 5650871 Japan

ISBN: (纸本)9781467389853

Because energy consumption in data centers is getting larger, the use of green energy for running data centers draws attention as a mean of reducing energy cost. The amount of green energy generated near data centers depends on environment of the data centers. When more green energy is generated, more jobs should be processed by using the generated green energy to reduce energy cost. This policy of scheduling job is called green-aware job scheduling. On the other hand, it is necessary to minimize delay of processing jobs from their deadline. In this paper, we propose a model of green-aware job scheduling based on 2-objective optimization problem to minimize energy cost and delay. The model shows that the green-aware job scheduling problem consists of linear objective functions, constraints of linear inequalities and integer constraints. By relaxing the integer constraints, it is possible to obtain approximated solutions of the problem.

关键词： Decentralized Data Centers Job Scheduling multi-objective optimization problem

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An Adaptive Evolutionary Algorithm Based on Decomposition with the Region Detection 2020

An Adaptive Evolutionary Algorithm Based on Decomposition wi...

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4th International Conference on High Performance Compilation, Computing and Communications (HP3C)

作者： Zhang, Rui Zhou, Yuren Zhao, Chunliang Sun Yat Sen Univ Guangzhou Peoples R China

ISBN: (纸本)9781450376914

The algorithms based on decomposition are regarded as a promising optimizer for the multi-objective optimization problems (MOPs). However, it is difficult for the algorithms based on decomposition to handle MOPs with the complicated feature, because they adopt the fixed weight vectors. In this paper, we propose an adaptive method with the region detection strategy for the decomposition-based evolutionary algorithm (aMOEA/D-RD) to adjust the weight vectors. In the proposed algorithm, some useless weight vectors, which are not associated to any solution in the successive generations, are found through the region detection method. Then these weight vectors are adaptively adjusted by the solutions in the most crowed subregion. After the adjustment of weight vectors, the distribution of the weight vectors can be more suit to approximate the true the Pareto optimal front of MOPs. Comparative experiments on benchmark with various geometric features have been performed and the simulation results show the effectiveness and the competitiveness of our proposal algorithm.

关键词： multi-objective evolutionary algorithms based on decomposition multi-objective optimization problem weight vector adaption hierarchical clustering

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