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30th Chinese Control and Decision Conference (CCDC)

作者： Hu Zhongquan Zhou Zhen Wang Hongbin Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Hebei Peoples R China

ISBN: (纸本)9781538612446

To solve the problem of premature convergence and search stagnation in traditional differential algorithm, this paper presents an adaptive dual model differential evolution algorithm based on cloud model (ADDEC). The variation model of ADDEC is produced by combining basic variation with cloud variation. And the adaptive operators are referenced respectively for scale factor and interactive probability during the operation of variation and crossover. "fhe robustness and the convergence rate of the algorithm are enhanced. Moreover the relationship between global search and local search of the algorithm is improved. The diversity of the population is guaranteed at the same time. It is tested by typical high dimension benchmark function and compared with other algorithms, and the results show that the ADDEC has better precision, high convergence speed and makes it easy to jump out the local optimal solution.

关键词： differential evolution algorithm Cloud model evolution strategy Adaptive

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Multi-objective Task Scheduling Optimization in Cloud Computing based on Genetic algorithm and differential evolution algorithm 37

Multi-objective Task Scheduling Optimization in Cloud Comput...

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37th Chinese Control Conference (CCC)

作者： Li, Yuqing Wang, Shichuan Hong, Xin Li, Yongzhi China Univ Geosci Sch Automat Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9789881563958

Reasonable task scheduling is a long-standing challenge in cloud computing. Scheduling process of cloud computing has the characteristics of dynamic nature, meanwhile the constraint of the target function from a single aspect cannot meet the needs of users. According to the above problem, a multi-objective task scheduling GA-DE algorithm based on Genetic algorithm (GA) and differential evolution (DE) is proposed in this paper, in which total time, cost and virtual machine load balancing three aspects are taken into account siniultaneously, In the phase of population initialization and crossover diversity of the initial population is increased by introducing individual different factors, which can prevent cross-operation of similar individuals and satisfy laws of inbreeding of natural relatives. The introduction of the DE in the GA mutation stage can not only give full play to the advantages of the global search ability of GA but also accelerate the algorithm produce optimal solution by utilizing advantage of local search ability and fast convergence speed of DE. The algorithm proposed in this paper is compared with GA and DE by cloud computing simulation experiments on CloudSim platform. Experimental result shows that this algorithm can optimize both GA and DE in terms of quality of service and virtual machine load balancing under the same conditions, which is proved to be an efficient task scheduling algorithm in cloud computing environment.

关键词： cloud computing task scheduling multi-objective Genetic algorithm differential evolution algorithm

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Optimized Self-Healing of Networked Microgrids using differential evolution algorithm

Optimized Self-Healing of Networked Microgrids using Differe...

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National Power Engineering Conference (NPEC)

作者： Meenakshi, N. Kavitha, D. Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai Tamil Nadu India

ISBN: (纸本)9781538638033

A framework for the independent Networked Microgrids (NMGs) in an transformative manner was proposed in this work. NMGs comprises of multiple Microgrids (MGs) are linked by a typical bus for supporting and interchanging the electric power with one other in this suggested configuration. It consists of normal and self-healing mode. These NMGs contain a two layer cyber communication network for information exchange and coordinate the self-healing process. Each NMGs contain a lower layer and operation of each MG are scheduled by energy management system (EMS). A number of EMS are linked by the upper layer for global optimization and communication. The aim of the first (normal) mode of performance is to schedule the dispatchable distributed generators (DGs) and loads to minimizing the operating cost and to minimize the supply and demand imbalance of each MG. This scheme switches to self-healing (next) mode when a fault or deficiency in generation happens in any one MG. The intention of self-healing mode of operation is to support the faulted portion of the system by the local power production capabilities of other normally operating MGs in an optimal cost. A differential evolution (DE) algorithm is utilized to share the portion of required power support to each MG in a scattered manner. The demanded power support will be provided by the resultant overall power output of NMGs. The efficiency of the scheduled methodology was demonstrated by the following test cases.

关键词： differential evolution algorithm Networked Microgrids (NMGs) Self-healing Distributed generators (DGs) Cyber communication network

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differential evolution algorithm for Computation of Dynamic ATC in Deregulated Power System

Differential Evolution Algorithm for Computation of Dynamic ...

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IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)

作者： Selvi, V. Agnes Idhaya Devaraj, D. Banu, R. Narmatha Pandiyan, M. Karuppasamy Kalasalingam Univ Dept EEE Virudunagar Tamil Nadu India Vellamal Coll Engn & Tech Dept EEE Madurai Tamil Nadu India

ISBN: (纸本)9781509047789

In restructured power system, determination of Available Transfer Capability (ATC) is an important issue. The ATC calculation is limited by system stability consideration. ATC calculated with dynamic stability limit is referred as Dynamic ATC (DATC). The Hopf bifurcation limit, associated with dynamic instability is considered in this paper as a limit for ATC calculation. In this paper, differential evolution algorithm (DEA) is applied to obtain accurate Hopf bifurcation point for DATC calculation. Dynamic ATC is calculated for bilateral and multilateral transaction using the proposed approach. The static ATC is also calculated for finding the governing criteria for each transaction. In order to identify the severe lines for each transaction, stability based contingency screening is performed. Based on contingency screening index severe lines are ranked and for first five severe lines the DATC is calculated. The results are compared with a Step by Step algorithm. Simulation is done for three different load scenarios namely static, dynamic (Induction machine model) and ZIP load. The proposed approach is tested on New England 10 machine 39 bus system for various transactions using PSAT Tool. Test results show the accuracy of proposed approach.

关键词： differential evolution algorithm Dynamic ATC Contingency Screening Index Hopf bifurcation Step by Step algorithm

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Performance Analysis of a differential evolution algorithm in Modeling Parameter Extraction of Optical Material

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SILICON 2017年第5期9卷 723-731页

作者： Saber, Md. Ghulam Ahmed, Ashik Sagor, Rakibul Hasan Islamic Univ Technol Dept Elect & Elect Engn Gazipur 1704 Bangladesh

Determination of accurate modeling parameters of optical materials prior to defining the materials in the simulation model is fundamentally important to obtain simulation results close to the experimental ones. However, extracting modeling parameters of optical materials is inherently difficult because it involves fitting both real and imaginary parts of the relative permittivity using a single set of parameters. In this paper, an evolutionary algorithm called differential evolution (DE) has been utilized to extract the optical modeling parameters of graphene oxide. The performance of DE to find the optimal results has been analyzed by using different objective functions and boundary values. Two objective functions are used out of which one is proposed by us. Root-means-square (RMS) deviation, a measure of accuracy of the numerically obtained results has been determined for each case. From the obtained results it has been found that the DE algorithm extracted the optical modeling parameters successfully with very small RMS deviation for both real and imaginary parts of the complex relative permittivity.

关键词： Optical parameter extraction differential evolution algorithm Graphene oxide Optimization

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Long-Term Scheduling of Large-Scale Cascade Hydropower Stations Using Improved differential evolution algorithm

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WATER 2018年第4期10卷 383-383页

作者： Wen, Xiaohao Zhou, Jianzhong He, Zhongzheng Wang, Chao Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China China Three Gorges Corp Beijing 100038 Peoples R China Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Hubei Peoples R China China Inst Water Resources & Hydropower Res Beijing 100038 Peoples R China

Long-term scheduling of large cascade hydropower stations (LSLCHS) is a complex problem of high dimension, nonlinearity, coupling and complex constraint. In view of the above problem, we present an improved differential evolution (iLSHADE) algorithm based on LSHADE, a state-of-the-art evolutionary algorithm. iLSHADE uses new mutation strategies "current to pbest/2-rand" to obtain wider search range and accelerate convergence with the preventing individual repeated failure evolution (PIRFE) strategy. The handling of complicated constraints strategy of e-constrained method is presented to handle outflow, water level and output constraints in the cascade reservoir operation. Numerical experiments of 10 benchmark functions have been done, showing that iLSHADE has stable convergence and high efficiency. Furthermore, we demonstrate the performance of the iLSHADE algorithm by comparing it with other improved differential evolution algorithms for LSLCHS in four large hydropower stations of the Jinsha River. With the applications of iLSHADE in reservoir operation, LSLCHS can obtain more power generation benefit than other alternatives in dry, normal, and wet years. The results of numerical experiments and case studies show that the iLSHADE has a distinct optimization effect and good stability, and it is a valid and reliable tool to solve LSLCHS problem.

关键词： energy hydropower stations differential evolution algorithm optimal scheduling epsilon-constrained method

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Peak-to-Average Power Ratio Reduction in Lifting Based Wavelet Packet Modulation Systems Using differential evolution algorithm

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WIRELESS PERSONAL COMMUNICATIONS 2017年第3期94卷 1073-1086页

作者： Bozkurt, Yuksel Tokur Taspinar, Necmi Gaziantep Univ Vocat Sch Tech Sci Dept Elect & Automat Gaziantep Turkey Erciyes Univ Dept Elect & Elect Engn Kayseri Turkey

Integer wavelet transform (IWT) is an alternative to fast Fourier transform (FFT) in orthogonal frequency division multiplexing (OFDM) systems. It serves implementation flexibility and performance improvement by diminishing high side lobes, sensitivity to time and frequency synchronization. However, high PAPR of the transmitted signals is also a significant problem for IWT as in FFT based OFDM. One of the methods used for reducing the peak-to-average power ratio (PAPR) is partial transmit sequences (PTS) and this method requires an exhaustive search to obtain optimum reduction. This study examines the PAPR reduction potential of differential evolution algorithm based PTS scheme in lifting based wavelet packet modulation (LBWPM) system. The simulation results indicate that remarkable PAPR reduction performance with a low computational load for LBWPM system can be achieved using the proposed differential evolution based PTS scheme.

关键词： differential evolution algorithm Lifting based wavelet packet modulation Partial transmit sequences Peak-to-average power ratio

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A Non-Dominated Sorting Cooperative Co-evolutionary differential evolution algorithm for Multi-Objective Layout Optimization

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IEEE ACCESS 2017年 5卷 14468-14477页

作者： Zhang, Zi-Hui Zhong, Chong-Quan Xu, Zhi-Zheng Teng, Hong-Fei Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

Different from traditional multi-objective evolutionary algorithms (MOEAS), multi-objective cooperative co-evolutionary algorithms (MOCCEAs) divide the decision variables into several subproblems to optimize. Solutions of each subproblem are evaluated by complete solutions formed through combining representative solutions from all subproblems. Therefore, the combination of representative solutions is a key issue in MOCCEAs. To improve the capability of MOCCEAs to complex multi objective optimization problems, we propose a non-dominated sorting cooperative co-evolutionary differential evolution algorithm (NSCCDE). The proposed NSCCDE uses an external archive for storing complete solutions to establish a new collaboration mechanism, which forms a complete solution by combining collaborators from each subpopulation as well as from the external archive. On the one hand, the external archive is updated continuously through non-dominated sorting of complete solutions, which is conducive to speeding up the convergence. On the other hand, the external archive evolves itself through spatial dispersal and mutation operation to increase the diversity. The performance of proposed NSCCDE is then evaluated on a suite of satellite module layout optimization problem. Experimental results demonstrate that the proposed algorithm outperforms NSCCGA and NSGA-II.

关键词： Multi-objective layout optimization cooperative co-evolution differential evolution algorithm satellite module

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A two-stage assessment method using damage locating vector method and differential evolution algorithm for damage identification of cross-ply laminated composite beams

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ADVANCES IN STRUCTURAL ENGINEERING 2017年第12期20卷 1807-1827页

作者： Du Dinh-Cong Trung Vo-Duy Nhan Nguyen-Minh Vinh Ho-Huu Trung Nguyen-Thoi Ton Duc Thang Univ Inst Computat Sci Div Construct Computat Ho Chi Minh City Vietnam Ton Duc Thang Univ Inst Computat Sci Div Computat Math & Engn Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Civil Engn Ho Chi Minh City Vietnam

This article proposes a two-stage damage identification method to identify the location and extent of multiple damages at individual layers in laminated composite beams. In the first stage, the damage locating vector method using normalized cumulative energy is employed to detect the locations of suspected damaged elements. In the second stage, the degree of the suspected damaged elements is determined by solving an optimization problem via differential evolution algorithm. To identify damage at a specific layer of the laminated composite beams, the layerwise theory is applied to analysis behavior of the beams. The performance of the method is assessed through two numerical examples with different damage scenarios. In addition, the effect of noise on the damage identification results is investigated.

关键词： damage identification methods damage locating vector method differential evolution algorithm laminated composite beam layerwise theory

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Research on the parameter inversion problem of prestack seismic data based on improved differential evolution algorithm

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2017年第4期20卷 2881-2890页

作者： Wu, Qinghua Zhu, Zhixin Yan, Xuesong WuHan Inst Technol Fac Comp Sci & Engn Wuhan 430205 Hubei Peoples R China China Univ Geosci Sch Comp Sci Wuhan 430074 Hubei Peoples R China

The parameter inversion technology composed by intelligent algorithm and AVO inversion for prestack seismic data provides a comparatively effective identification method for oil-gas exploration. However, traditionally intelligent iterative algorithm, such as, genetic algorithm, shows many disadvantages in solving this problem, including highly depending on initial model, fast convergence in algorithm and being easy to fall into local optimal. Therefore, an unsatisfied inversion performance is produced. In order to solve the above problems, this paper proposes a parameter inversion method based on improved differential evolution algorithm which is better in solving parameter inversion problems of prestack seismic data. In the proposed algorithm, aims at the Aki and Rechard approximation formula used specific initialization strategy, then the initialization parameter curve more smooth. Otherwise, the new algorithm has many advantages, such as, fast computing speed, simple operation, a low independence to initial model and good global convergence, this algorithm is the right choice in solving the parameter inversion problem based on pre-stack seismic data of real number encoding.

关键词： differential evolution algorithm Prestack seismic data Parameter inversion initialization strategy

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