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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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Optimal Filter Design Using differential evolution algorithm and Its Advanced Variants

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年

作者： Durmus, Burhanettin Unlu, Aybuke Ozyon, Serdar Temurtas, Hasan Kutahya Dumlupinar Univ Dept Elect & Elect Engn Kutahya Turkiye Kutahya Dumlupinar Univ Dept Comp Engn Kutahya Turkiye

Since passive elements such as resistors and capacitors used in active filter design change the gain and phase of the filter, their selection is an important issue. The ability of the filter to achieve a targeted quality factor depends on the selection of these components. The filter sections are cascaded to get closer to the ideal filter response;in this case, as the number of components increases, the computational complexity in selecting the optimum values increases. Moreover, in practical applications, the values of the filter components should be fixed to the discrete component values in the industrial component series. Thus, the problem turns into a discrete optimization problem that becomes more difficult and time-consuming. The use of metaheuristic algorithms in solving the problem is an alternative approach. This work propounds a survey on the differential evolution (DE) algorithm and its advanced variants utilized for the selection of optimal component values in filter design. Nine DE algorithms have been used to determine the optimal component values of the tenth-order Multi-Feedback topology Bessel filter. The performance of each algorithm has been evaluated in terms of convergence rate and solution accuracy. Statistical results show that success-history based adaptive DE with linear population size reduction (LSHADE) is superior to other DE variants and can reduce the filter quality factor error value to 4.64E-02 for E12 series, 6.45E-02 for E96 series and 2.23E-02 for E192 series. The obtained results show that LSHADE algorithm are an effective tool for the selection of optimal discrete component values in filter design, increasing computational speed and solution accuracy.

关键词： Active filter design Bessel filter differential evolution algorithm Multiple feedback topology

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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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Hybrid differential evolution algorithm Integrating Operations Research and Reinforcement Learning approaches 24

Hybrid Differential Evolution Algorithm Integrating Operatio...

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Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and Informatics

作者： Panagiotis G. Giannopoulos Gregory P. Chondrokoukis Thomas K. Dasaklis School of Social Sciences Hellenic Open University Patras Greece Department of Industrial Management and Technology University of Piraeus Piraeus Greece

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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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