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ETP/IITA Conference on Telecommunication and Information (TEIN 2010)

作者： Yong, Longquan Shaanxi Univ Technol Dept Math Hanzhong 723001 Peoples R China

ISBN: (纸本)9789881824257

We propose a novel method for the nonsmooth NP-hard absolute value equation (AVE). Under the condition that all the singular values of A exceed one, we construct a smooth function, called aggregate function, and replace the absolute value function by aggregate function. With this smoothing technique, AVE is transformed into a smooth nonlinear equation system, furthermore, an unconstrained differentiable optimization problem by introducing proper objective function. Then we apply differential evolution algorithm (DE) to solve AVE. Preliminary numerical examples indicate that the proposed algorithm is promising for solving AVE.

关键词： Absolute value equation differential evolution algorithm smooth function

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differential evolution algorithm of Basis Vector Scaling and Mirror Crossover 39

Differential Evolution Algorithm of Basis Vector Scaling and...

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39th Chinese Control Conference (CCC)

作者： Zhang, Chunmei Yang, Haibin Guo, Hongge Shi, Yanjun Taiyuan Univ Sci & Technol Coll Elect & Informat Engn Taiyuan 030024 Peoples R China

ISBN: (纸本)9789881563903

In order to avoid the problem of local optimality and low convergence accuracy, an improved differential evolution algorithm was proposed by combining the base vector scaling with the mirror crossover operation. Based on the basic difference algorithm, the base vector scaling coefficient is introduced to jump out of the local optimal value. In the process of crossover, mirror crossover is introduced to improve the probability of the better trial vector entering the selection step and promote the algorithm evolution. In order to verify the effectiveness of the improved differential evolution algorithm, the simulation results of 10 benchmark functions are compared with those of other algorithms in this paper. The results show that the proposed algorithm can avoid the algorithm from falling into local optimum and achieve better convergence performance.

关键词： differential evolution algorithm Base vector scaling Crossover operation Mirror Crossover

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differential evolution algorithm for the Optimization of the Vehicle Routing Problem in Logistics

Differential Evolution Algorithm for the Optimization of the...

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8th International Conference on Computational Intelligence and Security (CIS)

作者： Xu, Huan Wen, Jiechang Guangdong Univ Technol Sch Appl Math Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780769548968;9781467347259

The unidirectional logistics distribution vehicle routing problem with no time windows is considered. It contains the vehicle capacity restriction, the longest distance restriction and the full loaded vehicle. The solution must ensure the non-full loaded factor is the least and the total distance is the shortest. A multi-objective optimization mathematical model for the problem is established. And the differential evolution algorithm is proposed for this problem. The optimal solutions to the model are obtained by selecting the appropriate encoding method. The results of simulation show that the differential evolution algorithm is an effective way for solving the vehicle routing problem.

关键词： differential evolution algorithm logistics distribution multi-objective optimization vehicle routing problem

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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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Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the differential evolution algorithm

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1836-1848页

作者： Wei Qian Yanmin Wu Bo Shen School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuo 454000China College of Information Science and Technology Donghua UniversityShanghai 201620China

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution *** provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical *** conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack ***,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control ***,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

关键词： Adaptive memory event-triggered(AMET) differential evolution algorithm fuzzy optimization robust control interval type-2(IT2)fuzzy technique.

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Chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

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Journal of Central South University 2013年第4期20卷 950-959页

作者：范勤勤吕照民颜学峰郭美锦 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.

关键词： evolutionary computation dynamic optimization differential evolution algorithm Alopex algorithm self-adaptivity

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Unfolding neutron spectra from water-pumping-injection multilayered concentric sphere neutron spectrometer using self-adaptive differential evolution algorithm

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Nuclear Science and Techniques 2021年第3期32卷 41-51页

作者： Rui Li Jian-Bo Yang Xian-Guo Tuo Jie Xu Rui Shi Chengdu University of Technology Chengdu 610059China Sichuan University of Science and Engineering Zigong 643000China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province Chengdu 610059China

A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10^(-6)to avoid unnecessary ***,the crossover probability and scaling factor are self-adaptively *** Monte Carlo is used to simulate the readings of the WMNS under(1)a spectrum of Cf-252 and(2)its spectrum after being moderated,(3)a spectrum used for boron neutron capture therapy,and(4)a reactor ***,the measured neutron counts are unfolded using the *** uncertainties of the measured neutron count and the response matrix are considered in the SDENUA,which does not require complex parameter tuning or an a priori default *** results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS.

关键词： Water-pumping-injection multilayered spectrometer Neutron spectrum unfolding differential evolution algorithm Self-adaptive control

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Effective long short-term memory with differential evolution algorithm for electricity price prediction

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ENERGY 2018年 162卷 1301-1314页

作者： Peng, Lu Liu, Shan Liu, Rui Wang, Lin Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Hubei Peoples R China Xi An Jiao Tong Univ Sch Management Xian 710049 Shaanxi Peoples R China Harbin Inst Technol Shenzhen Grad Sch Shenzhen 518055 Peoples R China

Electric power, as an efficient and clean energy, has considerable importance in industries and human lives. Electricity price is becoming increasingly crucial for balancing electricity generation and consumption. In this study, long short-term memory (LSTM) with the differential evolution (DE) algorithm, denoted as DE LSTM, is used for electricity price prediction. Several recent studies have adopted LSTM with considerable success in certain applications, such as text recognition and speech recognition. However, problems in the application of LSTM to solving nonlinear regression and time series problems have been encountered. DE, a novel evolutionary algorithm that effectively obtains optimal solutions, is designed to identify suitable hyperparameters for LSTM. Experiments are conducted to verify the performance of the DE LSTM model under the electricity prices in New South Wales, Germany/Austria, and France. Results indicate that the proposed DE LSTM model outperforms existing forecasting models in terms of forecasting accuracies. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Long short-term memory differential evolution algorithm Electricity price prediction

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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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Transit Frequency Optimization in Bi-modal Networks Using differential evolution algorithm

TEKNIK DERGI

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TEKNIK DERGI 2022年第5期33卷 12601-12616页

作者： Mutlu, Mehmet Metin Aksoy, Ilyas Cihan Alver, Yalcin Adnan Menderes Univ Dept Civil Engn Aydin Turkey Karamanoglu Mehmetbey Univ Dept Civil Engn Karaman Turkey Ege Univ Dept Civil Engn Izmir Turkey

This study proposes a bi-level optimization model for the transit frequency setting problem in bi-modal networks. The objective of the upper-level problem is to obtain a solution set of bus line frequencies that provide the minimum total travel cost of the car and bus users. differential evolution (DE) algorithm is employed in the upper-level model to determine the optimal headways for a given route structure. The lower-level model is a congested multi-modal user equilibrium assignment model, which considers the interactions of car and bus flows, for determining joint mode/route preferences of the network users, which considers the interactions of car and bus flows. The developed model is tested on Mandl's benchmark network to evaluate its performance and applicability. The comparative experiments demonstrate that the proposed model leads to reductions in transportation costs. Also, the result of numerous optimization runs shows that DE performs well in finding similar frequency sets in independent optimizations.

关键词： Transit frequency setting problem bus frequency optimization multi-modal assignment differential evolution algorithm bi-level optimization

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