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Fitness and Collaborative Information-Driven differential evolution algorithm for Bound-Constrained and Real-World Application Problems

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2025年 1-35页

作者： Gupta, Shubham Singh, Shitu Gao, Shangce Motilal Nehru Natl Inst Technol Allahabad Dept Math Prayagraj 211004 India United Univ Dept Appl Sci Prayagraj 211012 Uttar Pradesh India Univ Toyama Fac Engn Toyama 9308555 Japan

The effectiveness of differential evolution (DE) is significantly impacted by the selection of the mutation operator and the setup of control parameters. However, their unique selection might not ensure the optimized search procedure that enables the algorithm to explore for a global optimal solution for the given optimization problem. Further, with this selection approach, the algorithm might suffer from the issues of getting stuck at local optima and premature convergence. To address these challenges, this paper proposes a new framework of the DE called fitness and collaborative information-driven DE (COLDE). In the COLDE, a novel mutation operator is proposed to strengthen the collaboration among elite and non-elite candidate solutions so that more promising offspring vectors can be generated. The scale factor parameters are adjusted according to the evolutionary state of candidate solutions engaged in the mutation operator, while the crossover operator is tuned based on the success rates of crossover parameters determined in the past evolutionary stage. Moreover, the population size is also reduced over the generations to discard the unfavorable candidate solutions. The validation of the proposed COLDE is conducted on the standard set of benchmark problems provided by the IEEE CEC2017 of real-parameter single-objective problems and eight real-world engineering optimization problems. A comparison of COLDE with other evolutionary algorithms using diverse performance metrics verifies its promising and competitive search efficiency against the compared algorithms.

关键词： Global optimization problems differential evolution algorithm Mutation operator Scale factor Crossover rate

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Indoor single station location technology for basketball court based on differential evolution algorithm for terminal multi-path fingerprint features

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Huang, Junxian Cao, Zhongwang Jimei Univ Chengyi Coll Xiamen Peoples R China Fujian Chuanzheng Commun Coll Coll Gen Educ 112 Shoushan Rd Fuzhou 350007 Fujian Peoples R China

With the increasing demand for location information, applications based on location information are also showing a diversified trend. Traditional indoor positioning technology often requires multiple base stations or relies on external devices to achieve positioning. To better avoid the problem of synchronization between sites in multi-site positioning systems, this study proposes a positioning method based on differential evolution algorithm in indoor non line of sight scenarios with known access point locations. By collecting multi-path fingerprint features from terminals and utilizing differential evolution algorithm for optimization, a single station positioning system based on differential evolution algorithm was established to achieve indoor single station positioning of basketball courts. The experiment shows that the positioning model can achieve 90% accuracy when the distance between R P is 0.8 m. In terms of positioning performance, a grid spacing of 0.5 meters is the best. Based on differential evolution algorithm, it can not only overcome the issue of error increase caused by multi-path effects but also improve positioning accuracy and stability. This study is essential for the design and optimization of indoor positioning systems.

关键词： differential evolution algorithm single-site localization technology fingerprints convolutional neural network feature collection

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Design Automation for Microwave Branch-line Couplers Using Artificial Neural Networks with Self-Adaptive differential evolution algorithm 6

Design Automation for Microwave Branch-line Couplers Using A...

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6th Australian Microwave Symposium, AMS 2025

作者： Chen, Tianqi Wu, Qiang Zhu, Xi University of Technology Sydney School of Electrical and Data Engineering Faculty of Engineering and IT Sydney Australia

ISBN: (纸本)9798350379969

The traditional method for designing branch-line couplers relies on a time-consuming labor-intensive trial-And-error process with multiple EM simulation iterations. This paper introduces a novel framework combining artificial neural networks with a self-Adaptive differential evolution algorithm (ANNs-SaDE) for automatic design. The effectiveness of this framework is demonstrated through the design of wideband three-stage couplers. © 2025 IEEE.

关键词： Artificial neural network branch-line coupler differential evolution algorithm

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Research on Active Disturbance Rejection Control of Small Modular Reactor Once-Through Steam Generator Based on differential evolution Optimization algorithm

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NUCLEAR TECHNOLOGY 2025年第5期211卷 974-993页

作者： Guo, Wei Shi, Bo Zhang, Tao Wu, Zhijiang Xiong, Guohua Peng, Minjun Harbin Engn Univ Coll Nucl Sci & Technol Harbin 150006 Heilongjiang Peoples R China China Nucl Power Technol Res Inst TT&P Res Inst Shenzhen 518000 Peoples R China

The pressure control of once-through steam generator (OTSG) is critical for the operation and safety of small modular reactors. However, the dynamics of the OTSG are quite nonlinear, time varying, and uncertain. Classical control methods face significant challenges in keeping the pressure within acceptable limits in an environment with frequent load variations and multiple sources of external *** this paper, a robust control strategy based on active disturbance rejection control (ADRC) optimized by the differential evolution (DE) algorithm is proposed to satisfy the requirements of steam pressure control in an optimum and efficient way. First, a lumped parameter model for the OTSG is developed based on the notion of moving boundaries and linearized to introduce a transfer function model for control design purposes. Then a feedforward cascade control system based on an ADRC controller and a proportional integral differential (PID) controller is designed, which mainly consists of a pressure ADRC controller, a feedwater PID controller, and a feedforward *** improve the pressure control performance and parameter tuning efficiency of the OTSG control system, a DE algorithm is applied to optimize the ADRC parameters, and the frequency domain and time domain characteristics are compared with particle swarm optimization and the genetic algorithm. Transient simulation experiments were used to evaluate the control performance at 100%, 50%, and 25% power levels, respectively. Moreover, a performance robustness criterion is proposed to demonstrate the robust stability of the ADRC, and the robustness metric is compared with that of the PID control schemes. The simulation results show that DE-ADRC control strategy has better set point tracking, interference rejection, and robust stability than DE-PID control strategy.

关键词： Once-through steam generator lumped parameter model active disturbance rejection control parameter tuning differential evolution algorithm

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differential evolution algorithm with dynamic multi-population applied to flexible job shop schedule

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ENGINEERING OPTIMIZATION 2022年第3期54卷 387-408页

作者： Cao, Yang Shi, Haibo Chang, DaLiang Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang Peoples R China Chinese Acad Sci Inst Robot Shenyang Peoples R China Chinese Acad Sci Inst Intelligent Mfg Shenyang Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Key Lab Network Control Syst Shenyang Peoples R China Shenyang Jianzhu Univ Informat & Control Engn Fac Shenyang Peoples R China

This article proposes a novel differential evolution algorithm based on dynamic multi-population (DEDMP) for solving the multi-objective flexible job shop scheduling problem. In DEDMP, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of the subpopulation is dynamically adjusted based on the last search experience. Furthermore, DEDMP is adaptive based on two search strategies, one with strong exploration ability and the other with strong exploitation ability. The selection probability of each search strategy is also dynamically adjusted according to the success rate. Furthermore, the proposed algorithm adopts newly designed mutation and crossover operators and it can directly generate feasible solutions in the search space. To evaluate the performance of DEDMP, DEDMP is compared with some state-of-the-art algorithms on benchmark instances. The experimental results show that DEDMP is better than or at least competitive with other outstanding algorithms.

关键词： Flexible job shop scheduling problem differential evolution algorithm multi-objective optimization multiple subpopulations strategy adaptation

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differential evolution algorithm for dynamic structural identification

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JOURNAL OF EARTHQUAKE ENGINEERING 2008年第5期12卷 800-821页

作者： Savoia, Marco Vincenzi, Loris Univ Bologna DISTART Struct Engn I-40136 Bologna Italy

In the present article, differential evolution algorithm is used to perform structural identification of mass and stiffness properties of civil structures from dynamic test results. Identification is performed initially starting from exact values of modal parameters (frequencies and mode shapes). Robustness of the algorithm is then tested by adopting pseudo-experimental input data, obtained by adding to exact data some statistic scattering, representing experimental measurement error. Different objective functions are adopted in identification procedure, and results are compared with those obtained adopting classical gradient method. The method is used to identify masses, elastic moduli, and stiffnesses of external constraints of a RC frame structure and a steel-concrete bridge. Numerical results confirm that adopting both frequencies and mode shapes instead of frequencies only strongly increases sensitivity of objective function to identification parameters. Scattering of identified parameters is much smaller, with coefficient of variation of the same order of magnitude of that of pseudo-experimental data used as input values in dynamic identification procedure.

关键词： structural identification differential evolution algorithm optimization dynamic tests

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differential evolution algorithm Aided Turbo Channel Estimation and Multi-User Detection for *** Systems in the Presence of FEXT

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IEEE ACCESS 2018年 6卷 33111-33128页

作者： Zhang, Jiankang Chen, Sheng Zhang, Rong Al Rawi, Anas F. Hanzo, Lajos Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England King Abdulaziz Univ Jeddah 21589 Saudi Arabia British Telecommun PLC Ipswich IP5 3RE Suffolk England

The ever-increasing demand for broadband Internet access has motivated the further development of the digital subscriber line to the *** standard in order to expand its operational band from 106 to 212 MHz. Conventional far-end crosstalk (FEXT)-based cancellers falter in the upstream transmission of this emerging *** system. In this paper, we propose a novel differential evolution algorithm (DEA)-aided turbo channel estimation (CE) and a multi-user detection (MUD) scheme for the *** upstream, including the frequency band up to 212 MHz, which is capable of approaching the optimal Cramer-Rao lower bound of the channel estimate, whilst approaching the optimal maximum likelihood MUD's performance associated with perfect channel state information and, yet, only imposing about 5% of its computational complexity. Explicitly, the turbo concept is exploited by iteratively exchanging information between the continuous value-based DEA-assisted channel estimator and the discrete value-based DEA MUD. Our extensive simulations show that 18-dB normalized mean square error gain is attained by the channel estimator and 10-dB signal-to-noise ratio gain can be achieved by the MUD upon exploiting this iteration gain. We also quantify the influence of the CE error, the copper length, and the impulse noise. This paper demonstrates that the proposed DEA-aided turbo CE and MUD scheme is capable of offering near-capacity performance at an affordable complexity for the emerging *** systems.

关键词： Digital subscriber line far-end crosstalk G.fast upstream vectoring turbo channel estimation and multi-user detection differential evolution algorithm

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differential evolution algorithm for emission constrained economic power dispatch problem

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ELECTRIC POWER SYSTEMS RESEARCH 2010年第10期80卷 1286-1292页

作者： Abou El Ela, A. A. Abido, M. A. Spea, S. R. Menoufiya Univ Fac Engn Dept Elect Engn Menoufia Egypt King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia

In this paper, a differential evolution (DE) algorithm is developed to solve emission constrained economic power dispatch (ECEPD) problem. Traditionally electric power systems are operated in such a way that the total fuel cost is minimized regardless of emissions produced. With increased requirements for environmental protection, alternative strategies are required. The proposed algorithm attempts to reduce the production of atmospheric emissions such as sulfur oxides and nitrogen oxides, caused by the operation of fossil-fueled thermal generation. Such reduction is achieved by including emissions as a constraint in the objective of the overall dispatching problem. A simple constraint approach to handle the system constraints is proposed. The performance of the proposed algorithm is tested on standard IEEE 30-bus system and is compared with conventional methods. The results obtained demonstrate the effectiveness of the proposed algorithm for solving the emission constrained economic power dispatch problem. Published by Elsevier B.V.

关键词： Economic power dispatch differential evolution algorithm Fuel cost minimization Emission constraint Environmental issues

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differential evolution algorithm based tilt integral derivative control for LFC problem of an interconnected hydro-thermal power system

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JOURNAL OF VIBRATION AND CONTROL 2018年第17期24卷 3952-3973页

作者： Topno, Pretty Neelam Chanana, Saurabh Natl Inst Technol Dept Elect Engn Kurukshetra 136119 Haryana India

Conventional control techniques such as proportional integral (PI) control and proportional integral derivative (PID) control are widely used as the load frequency controller in power system control applications;however, the increase in complexity of the power system is degrading the performance of classical control. Therefore, in this paper a new control approach using fractional calculus has been proposed for the load frequency control problem of two-area hydro-thermal power system. The paper presents an interconnected hydro-thermal power system working under different operating conditions introduced in the form of various nonlinearities. Four case studies have been presented in this paper considering transient analysis with (i) different loading conditions, (ii) parameter variations, (iii) different nonlinearities (governor dead band nonlinearity, time delay and generation rate constraints), and (iv) superconducting magnetic energy storage (SMES) device. A tilt integral derivative (TID) control has been presented as a secondary controller to stabilize the frequency deviations occurring in the two-area power system with the above-mentioned different operating conditions. The parameters of TID controller have been optimized using a differential evolution algorithm which solves an optimization problem formulated using the integral of time-weighted absolute error (ITAE) performance index. In addition, a comparison of dynamic system response obtained using TID control and PID control has been presented, which focusses on the better performance of TID control over PID control in an interconnected power system.

关键词： differential evolution algorithm generation rate constraint governor dead band load frequency control time delay PID control SMES device TID control

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differential evolution algorithm for optimal reactive power dispatch

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ELECTRIC POWER SYSTEMS RESEARCH 2011年第2期81卷 458-464页

作者： Abou El Ela, A. A. Abido, M. A. Spea, S. R. Menoufiya Univ Fac Engn Dept Elect Engn Delta Egypt King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia

Reactive power dispatch (RPD) is one of the important tasks in the operation and control of power system. This paper presents an efficient and reliable evolutionary-based approach to solve the RPD problem. The proposed approach employs differential evolution (DE) algorithm for optimal settings of RPD control variables. The proposed approach is examined and tested on the standard IEEE 30-bus test system with different objectives that reflect power losses minimization, voltage profile improvement, and voltage stability enhancement. The simulation results of the proposed approach are compared to those reported in the literature. The results demonstrate the potential of the proposed approach and show its effectiveness and robustness to solve the RPD problem. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.

关键词： Reactive power dispatch differential evolution algorithm Fuel cost minimization Voltage profile improvement Voltage stability enhancement

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