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20th International Conference on Advanced Communication Technology (ICACT)

作者： Wu, Jie Li, Hongchun Xu, Yi Tian, Jun Fujitsu Res & Dev Ctr Co Ltd Beijing Peoples R China

ISBN: (纸本)9791188428014

multi-hop wireless networks have advantages over the single-hop ones in terms of reliability and coverage range. Moreover, the capacity of multi-hop wireless network can be substantially increased via multiple radios tuned to non-overlapping channels. However, the channel allocation, network interface cards assignment and routing remain challenging due to the interference of the neighboring transmissions. These three problems have proved to be a NP-hard problem. Previous studies separating the routing from the channel allocation, instead of considering the three problems as a whole, cannot get the overall optimal solution. In this work, we employ an improved multi-objective genetic algorithm to optimize the channel allocation, interface assignment and the routing, so as to minimize the overall network interference. The proposed algorithm includes two parts: 1) dynamic genetic mutation based on diversity measure;and 2) elite preservation based on ideal points. In order to eliminate illegal solutions, a new individual encoding method is proposed. In addition, an interference model taking into account the effects of channel separation and the traffic of neighbor links is applied to evaluate the quality of the interference of the network. Finally, a fitness function is defined to obtain the best search results. Simulation results show that our improved multi-objective genetic algorithm can reduce the interference and cost of total network compared to the standard genetic algorithm.

关键词： multi-objective genetic algorithm channel allocation interface assignment routing multi-hop wireless network

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A New multi-objective Hybrid Gene Selection algorithm for Tumor Classification Based on Microarray Gene Expression Data

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS 2023年第4期22卷 2350019-2350019页

作者： Li, Min Wu, Bangyu Deng, Shaobo Lou, Mingzhu Nanchang Inst Technol Sch Informat Engn 289 Tianxxaing Rd Nanchang Jiangxi Peoples R China

Tumor classification based on microarray gene expression data is easy to fall into overfitting because such data are composed of many irrelevant, redundant, and noisy genes. Traditional gene selection methods cannot achieve satisfactory classification results. In this study, we propose a novel multi-target hybrid gene selection method named RMOGA (ReliefF multi-objective genetic algorithm), which aims to select a few genes and obtain good tumor recognition accuracy. RMOGA consists of two phases. Firstly, ReliefF is used to select the top 5% subset of genes from the original datasets. Secondly, a multi-objective genetic algorithm searches for the optimal gene subset from the gene subset obtained by the ReliefF method. To verify the validity of RMOGA, we conducted extensive experiments on 11 available microarray datasets and compared the proposed method with other previous methods. Two classical classifiers including Naive Bayes and Support Vector Machine were used to measure the classification performance of all comparison methods. Experimental results show that the RMOGA algorithm can yield significantly better results than previous state-of-the-art methods in terms of classification accuracy and the number of selected genes.

关键词： Gene selection reliefF multi-objective genetic algorithm microarray gene expression data

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Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

Dynamic Scheduling of Virtual Cellular Based on Rolling Wind...

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2017 the 2nd International Conference on Mechatronics Engineering and Information Technology(ICMEIT 2017)

作者： Wenmin Han Yi Yu Ting Chen Zhengyi Li School of Economics and Management Jiangsu University of Science and Technology

ISBN: (纸本)9781510840683

Aiming at the dynamic scheduling problem of virtual cellular generated by the random arrival of new tasks,combined with the rolling window technology,the decision-making judgment based on the order completion trigger and the machine idle state trigger is put *** the same time,the dynamic random scheduling period is divided into continuous interval of static *** a non-linear multi-objective 0-1 integer programming model is proposed,which is based on the maximum completion time,the weighted total delay and the initial scheduling degree of deviation as the *** multi-objective genetic algorithm is used to solve the ***,taking the shipbuilding as an example,the feasibility and effectiveness of the rescheduling model are verified.

关键词： dynamic scheduling of virtual cellular rolling window multi-objective genetic algorithm

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Optimised Decision Making of Transportation Infrastructure Asset Management

Optimised Decision Making of Transportation Infrastructure A...

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世界交通运输工程技术论坛（WTC2021）

作者： Jiarong Li Chang'an University Department of Traffic Engineering

After more than 30 years of rapid development and construction,the transportation infrastructure achievements in China have attracted worldwide *** the other hand,the demand for Transportation Infrastructure Asset Management(TIAM)is growing quickly and strongly,and the rapid,safe and high-density traffic development trends have placed new demands on transportation infrastructure construction and *** the durable period of the pavement,it is still necessary to continue investing a large amount of funds to maintain and rebuild the pavement to keep their good performance,but the funds are not always available,so how to allocate the maintenance funds reasonably and keep the pavement in a good condition at the same time has become a hotpot,there are many decision-making methods to deal with it,but all of them have some deficiencies,this paper utilizes the inherent parallel mechanism and the characteristics of global optimization of genetic algorithm(GA),proposes a multi-objective genetic algorithm(MOGA)to simulate the problem of TIAM as a biological evolution problem,and by comparing the fitness of each generation of individuals to generate a new generation,in subsequent iterations,the generation is constantly replaced with a high fitness alternative to a low fitness value,so that after several generations,the best can be *** optimization result of a case study shows that the application of this algorithm in TIAM is successful and effective.

关键词： Transportation infrastructure asset management Optimised decision-making multi-objective genetic algorithm Large scale road network

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A NSGA-Ⅱ based Peak Load Shifting Optimization Method for Customers with Distributed Generators Considering Time-of-use Price

A NSGA-Ⅱ based Peak Load Shifting Optimization Method for C...

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第37届中国控制会议

作者： Hao Zhou Min Ding Bo Hu Qingyi Wang Zhili Tan Danyun li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute Co. LTD.

With the extensive use of distributed generation, the traditional demand response analysis cannot meet the current *** paper proposes a NSGA-II based peak load shifting optimization method for customers with distributed generators considering time-of-use price. Firstly, a fuzzy classification method divides the daily power into three time segments,peak hours, flat hours and valley hours. Secondly, on the basis of the time-of-use price, a peak load shifting optimization model is built with constraints and the objectives of minimizing the peak load, maximizing the valley load, and minimizing the peakvalley difference. Then, a NSGA-II based optimization method solves the optimal model and obtains the optimal electricity prices of different time segments to shift the peak load and the valley load. Finally, the simulation results shows the effectiveness of the proposed method.

关键词： Distributed Generation Demand Respond Time-of-use Price multi-objective genetic algorithm

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multi-satellite Observation Scheduling for Large Area Disaster Emergency Response

Multi-satellite Observation Scheduling for Large Area Disast...

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The ISPRS Technical Commission III Midterm Symposium on "Developments, Technologies and Applications in Remote Sensing"

作者： X.N.Niu H.Tang L.X.Wu Key Laboratory of Environment Change and Natural Disaster Ministry of EducationBeijing Normal University Beijing Key Laboratory of Environmental Remote Sensing and Digital Cities Beijing Normal University School of Geosciences and Info-Physics Central South University

Timely acquiring remote sensing data is very important for rapid response to disasters. Satellite task scheduling aiming at making an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HASGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

关键词： Disaster Emergency Response Area Tasks Decomposition multi-satellite Scheduling multi-objective genetic algorithm

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The Portfolio Model Based on Temporal Convolution Networks and the Empirical Research on Chinese Stock Market 2021

The Portfolio Model Based on Temporal Convolution Networks a...

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2021 5th International Conference on Computer Science and Artificial Intelligence

作者： Rui Zhang Zuoquan Zhang Marui Du Xiaomin Wang Beijing Jiaotong University China

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Real-time online Compensation the Nonlinearities and Uncertainties in Missile Servo Control System

Real-time online Compensation the Nonlinearities and Uncerta...

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第27届中国控制与决策会议

作者： Zhang Kun feng Rao Da wei Zhu Jian bo Duan Li hua Luoyang Optoelectronic Technology Development Center

ISBN: (纸本)9781479970186

To restrain the influences of the nonlinearities and uncertainties in missile servo control systems,the active disturbance rejection control(ADRC) technique is introduced to real-time online estimate and compensate these *** to the problem of the difficulties in tuning ADRC parameters,an improved multi-objective genetic algorithm is adopted to solve the complete set of Pareto solutions for the control parameters,then a multi-criteria decision making algorithm based on utility function is chosen to determine the fittest *** a test platform using TMS320C28346 floating-point DSP as control core is built to verify the research *** experimental results show that the optimal ADRC parameter is appropriate for the servo control *** system tracks the input commands smoothly and reliably,and has good robustness and adaptability to nonlinearities and parameters *** the strategy for tuning the ADRC parameters is practical and feasible.

关键词： Nonlinearity and Uncertainty Active Disturbance Rejection Control multi-objective genetic algorithm

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A multi-objective SCHEDULING STRATEGY BASED ON MOGA IN CLOUD COMPUTING ENVIRONMENT

A MULTI-OBJECTIVE SCHEDULING STRATEGY BASED ON MOGA IN CLOUD...

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2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems

作者： Zhou Lei Jinfeng Xiang Zhebo Zhou Feng Duan Yu Lei School of Computer Engineering and Science Shanghai University Department of Computer Science and Engineering The University of Texas at ArlingtonArlingtonTX 76019USA

Cloud service providers usually utilize the resource in the data center to offer cloud computing service which needs to satisfy the demand of different customers. The load among the physical servers in the data center needs to be balanced to avoid hotspot and improve resource utility. In this paper we present a load balancing system and design an algorithm base on MOGA to get a new mapping relationship between physical machines and VMs. By a set of migrating operations of VMs the problem of load imbalance are solved. Through comprehensive simulations, the experimental results demonstrate that our proposed approaches can significantly improve the resource utilization when system load is stable variant.

关键词： Virtual machine multi-objective genetic algorithm Mapping policy Load balance

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Large System multi-objective Model of Optimal Allocation for Water Resources in Jiansanjiang Branch Bureau

Large System Multi-objective Model of Optimal Allocation for...

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第五届国际计算机与计算技术在农业中的应用研讨会

作者： Ping Lv Dong Liu School of Water Conservancy & Civil Engineering Northeast Agricultural University

According to the imbalance development and utilization of water resources,water shortages and other issues in Sanjiang Plain,taking Jiansanjiang branch bureau as an example,the multi-objective optimal allocation model of water resources is established with goal of maximum economic and social *** surface water,groundwater and transit water are considered overall and different water demands in industry,life and agriculture are satisfied can we realize the rational allocation of regional water *** large system decomposition-coordination theory and multiobjective genetic algorithm are applied to solve the *** optimization results showed that,the water shortage situation in Jiansanjiang branch bureau is improved in planning years and surface water supply capacity can be increased gradually and groundwater resources can be effectively *** optimal allocation model and solution method are effective and feasible,and the optimal allocation results are *** research can provide scientific basis for rational development and utilization of water resources in Jiansanjiang branch bureau and Sanjiang Plain.

关键词： Jiansanjiang branch bureau optimal allocation of water resources multi-objective genetic algorithm large system decomposition-coordination

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