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A multi-objective optimization metaheuristic hybrid technique for forecasting the electricity consumption of the UAE: A grey wolf approach

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JOURNAL OF FORECASTING 2025年第1期44卷 242-252页

作者： Karathanasopoulos, Andreas Lo, Chia Chun Sovan, Mitra Osman, Mohamed von Mettenheim, Hans-Jorg Skander, Slim Univ Dubai Dubai Business Sch Dubai U Arab Emirates Huatai Futures Co Ltd Guangzhou Peoples R China Doctoral Think Tank Macau Peoples R China Westminster Univ London England Ipag Business Univ Paris France

By implementing a multi-objective optimization approach in forecasting, we introduce three optimization models grey wolf optimizer, genetic algorithm, and differential evolution algorithm combined with multilayer perceptron neural networks and support vector machines to predict electricity consumption in the UAE. The hybrid models' accuracy and efficiency were evaluated using various forecasting metrics. This study's contributions are threefold: it is the first to employ such a sophisticated hybrid approach, particularly using the recently introduced grey wolf optimizer, it compares optimization techniques with the established Pearson correlation-based method for dimensionality reduction and it represents one of the most extensive macroeconomic forecasts in the UAE using multi-objective heuristic hybrid optimization methods. Our findings indicate that the grey wolf optimizer significantly outperforms all other models, followed by the genetic algorithm.

关键词： differential evolution algorithm genetic algorithm Grey wolf macroeconomic forecast statistical measures

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A novel hybrid ESO-DE-WHO algorithm for solving real-engineering optimization problems

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2025年第1期16卷 254-309页

作者： Panigrahy, Damodar Samal, Padarbinda SRM Inst Sci & Technol Coll Engn & Technol Dept Elect & Commun Engn Chennai 603202 Tamilnadu India KIIT Deemed Be Univ Sch Elect Engn Bhubaneswar India

The proposed algorithm is based on the combination of enhanced seagull optimization (ESO) algorithm, differential evolution (DE) algorithm, wild horse optimization (WHO) algorithm with probability matrix to solve optimization problems. The seagull optimized algorithm is enhanced to avoid premature convergence. A probabilistic matrix with an equal value of each location is generated having 3 columns and the number of populations as rows. The three columns represent enhanced seagull optimization algorithm, differential evolution algorithm, and wild horse optimization algorithm respectively. Initial decision vector is generated in the bound. The probabilistic matrix after each iteration is updated with respect to minimum fitness value among 3 algorithms for each population. The decision vector for the next stage is decided based on the highest value of probability matrix. This stage improves the learning process and reduces the convergence rate. The updation of the probabilistic matrix and selection of decision vector for the next stage is continued until certain criteria are achieved. The optimized result of the proposed algorithm is the final minimum value. The proposed methodology is validated by comparing mean, standard deviation, best and worst value with ten other algorithms for 95 functions of CEC-2021. These algorithms are Archimedes optimization, wild horse optimizer, cuckoo search, differential evolution, black widow optimization, seagull optimization, whale optimization, arithmetic optimization, coot optimization, enterprise development (ED), hybrid jellyfish search and particle swarm optimization (HJPSO), modified lightning search algorithm (MLSA), polar lights optimizer (PLO), and parrot optimizer algorithm. The efficiency of the proposed methodology was also validated statistically with the ten methodologies The proposed methodology is also verified by five real-time engineering optimization problems. The results show better performance of the proposed al

关键词： CEC-2021 differential evolution algorithm Seagull optimization algorithm Wild horse optimizer algorithm

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Gas system scheduling strategy for steel metallurgical process based on multi-objective differential evolution

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INFORMATION SCIENCES 2024年 654卷

作者： Feng, Lili Peng, Jun Huang, Zhaojun Cent South Univ Sch Automat Changsha 410083 Peoples R China Cent South Univ Sch Comp Sci & Engn Changsha 410083 Peoples R China Hunan Valin Lianyuan Steel Co Ltd Loudi 417009 Peoples R China

Effective gas system scheduling is vital for ensuring the safe operation and energy efficiency of steel production. However, the dynamic and cyclical nature of gas generation and consumption leads to fluctuations in gas network pressure and gas holder levels. To address this issue, this paper proposes a novel strategy for gas system scheduling based on multi-objective differential evolution. The originality lies in fully considering the workload of operators, effectively reducing the workload while ensuring gas network stability. We analyze the composition of the gas system and design a scheduling scheme. Subsequently, a novel gas holder level model based on mechanism analysis is established, which calculates the gas holder level by analyzing the volume and pressure of the gas. Then, a gas system scheduling model with a new objective function based on a multi-objective differential evolution algorithm is provided. By comparing with the two recent methods, this method reduced the number of adjustments by 13.9% and 9.75%, respectively, effectively reducing the workload while ensuring gas system stability. Through statistical analysis for eight consecutive months, the results show that this method can reduce the gas emission rate from 1.34% to 0.88%, demonstrating its correctness and effectiveness.

关键词： Steel metallurgy process Gas system Scheduling strategy differential evolution algorithm

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A crashworthiness optimization method of subway underframe structures based on the differential evolution of the weighted graph representation

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2024年第4期67卷 62-62页

作者： Yao, Shuguang Zhou, Yili Xing, Jie Xu, Ping Huang, Qi Zou, Fan Cent South Univ Key Lab Traff Safety Track Minist Educ Changsha 410075 Peoples R China Joint Int Res Lab Key Technol Rail Traff Safety Changsha 410075 Peoples R China Natl & Local Joint Engn Res Ctr Safety Technol Rai Changsha 410075 Peoples R China

The crashworthiness optimization of the subway end structure is essentially a topology-shape-size collaborative optimization problem of a composite structure under collision conditions. To this end, a rapid multivariate co-optimization method based on weighted graph model and differential evolution algorithm is proposed. The underframe configuration is mapped as a weighted graph and then represented by mathematical matrices. By parameter inversion, a basic parametric simplified finite element model is established and validated by the detailed finite element model and the impact test. Three different configuration optimizations are accomplished and compared to prove the efficiency of the proposed method. The research results of this paper provide a reliable method and a reference for the further development of the crashworthiness optimization for complex structures.

关键词： Subway underframe structure Crashworthiness Collaborative optimization Weighted graph differential evolution algorithm

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Do existing split failure metrics accurately reflect pedestrian operation at signalized intersections?

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International Journal of Transportation Science and Technology 2024年第1期13卷 270-283页

作者： Ferdousy Runa S.Ilgin Guler Vikash V.Gayah Traffic Engineer WhitmanRequardt&AssociatesLLPUnited States The Pennsylvania State University University ParkPAUnited States

Signal timings at signalized intersections are frequently optimized by considering com monlyusedvehicle delay *** is generally believed that reducing the average number of stops can also decrease the average vehicle ***,the aim of this research is to address the question:“Can similar performance outcomes be achieved through the Minimization of Average Vehicle Delay(MAVD)and the Minimization of Average Number of Stops(MANS)?”The first phase of the study entails the creation of two distinct signal timing optimization models based on the Akcelik average vehicle delay and average number of stops ***,scripts were developed in MATLAB to identify the optimal signal timings for both approaches utilizing the differential evolution *** the third phase,30 traffic scenarios were generated,each varying in overall traffic vol umes at the ***,the signal timings derived from the MAVD and MANSapproaches were applied independently to these scenarios,and performance indica tors(average vehicle delay and average number of stops)were *** results reveal that the utilization of MANS-based signal timings instead of MAVD may lead to an increase in average vehicle delays of up to 113.55%.Additionally,it is demonstrated that when MAVD-based signal timings are applied instead of MANS,the average number of stops can increase by up to 16.28%.Finally,it is concluded that as the overall traffic volume at the intersection increases,these growth rates tend to decrease.

关键词： Signalized intersection Average vehicle delay Average number of stops differential evolution algorithm Optimization

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Explainable prediction of surface roughness in multi-jet polishing based on ensemble regression and differential evolution method

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 249卷

作者： Wang, Yueyue He, Zongbao Xie, Shutong Wang, Ruoxin Zhang, Zili Liu, Shimin Shang, Suiyan Zheng, Pai Wang, Chunjin Jimei Univ Sch Comp Engn Xiamen 361021 Fujian Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn State Key Lab Ultraprecis Machining Technol Hung HomKowloon Hong Kong Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hung Hom Kowloon Hong Kong Peoples R China

Surface roughness is a critical parameter for quantifying the surface quality of a workpiece. Accurate surface roughness prediction can significantly influence the overall quality of the final components by reducing costs and enhancing productivity. Although various prediction methods have been explored in previous research, less attention has been given to explainable prediction methods for surface roughness. This paper proposes a surface roughness prediction model based on the differential evolution (DE) algorithm with ensemble learning. It aims to elucidate the intrinsic correlation between processing parameters and surface roughness values in Multi-Jet Polishing (MJP) using explainable analysis methods. The proposed Ensemble Regression with differential evolution (ERDE) algorithm comprises two main modules: data processing and analytics, and ensemble model prediction. These modules investigate the surface roughness of MJP from the data and model levels, respectively. To validate the effectiveness of ERDE, MJP experiments were conducted on three-dimensional printed components of 316L stainless steel. The experimental data indicated that ERDE outperforms other existing algorithms, reducing the mean absolute percentage error by approximately 42 %.

关键词： Surface roughness prediction Polishing Explainable analysis Ensemble learning differential evolution algorithm Ultra-precision machining

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Modeling of zirconium alloy cladding corrosion behavior based on neural ordinary differential equation

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NUCLEAR ENGINEERING AND TECHNOLOGY 2025年第3期57卷

作者： Zhang, Tao Jiao, Yongjun Liu, Zhenhai Xing, Shuo Wang, Haoyu Zhang, Kun Li, Yuanming Nucl Power Inst China State Key Lab Adv Nucl Energy Technol Chengdu 610213 Peoples R China

Current zirconium alloy cladding corrosion models are mainly semi-empirical and show significant dispersion when compared to measured data. This study introduces neural ordinary differential equation (neural ODE) to model corrosion behavior, utilizing data-model fusion approach for network training. Initially, a semi-empirical model for zirconium alloy cladding corrosion is established through differential evolution algorithm, generating a large dataset for pre-training the neural network. The network is then fine-tuned using measured data. These methods effectively address the challenges of sparse cladding corrosion data and data available only at fixed time points, resulting in a more accurate model. The results show that the differential evolution algorithm can identify a set of appropriate parameters for the semi-empirical model, achieving a standard deviation of 0.040. The neural ODE model demonstrates even higher accuracy, reducing the standard deviation to 0.031 and improving accuracy by approximately 25%. Additionally, the model demonstrates excellent generalization capacity on other time points and new power histories.

关键词： Cladding corrosion model differential evolution algorithm Neural ordinary differential equation Data-model fusion driven

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Particle Distribution Measurement of Highly Concentrated Emulsions Based on Ultrasonic Extended Coupled Phase Model

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RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING 2024年第4期60卷 378-388页

作者： Hou, Huaishu An, Yuxiang Yun, Han Tang, Chenhuai Shanghai Inst Technol Dept Mech Engn Shanghai 201418 Peoples R China Hainan Boiler Pressure Vessel & Special Equipment Dept Boiler Haikou 570205 Peoples R China Shanghai Inst Special Equipment Inspection & Tech Dept Boiler Inspection Inst Shanghai 200062 Peoples R China

This paper introduces a method for measuring solute particle size in solution. The working principle of this method is to characterize the particle size by using the ultrasonic extended coupled phase model combined with the acoustic attenuation coefficient of the solution. In the ultrasonic detection of highly concentrated emulsion particles, the inter-particle interaction, namely the structural loss, becomes the main factor affecting the ultrasonic attenuation. In this study, micron-sized emulsions with 10, 15, and 20% concentration were experimentally detected by the extended coupled-phase model, and the inverse calculation of the particle size distribution was carried out using a differential evolutionary algorithm. The detection results showed an average error of 4.266% compared with those of laser particle sizer. The results show that ultrasonic detection based on the extended coupled phase model combined with differential evolution inversion algorithm can achieve accurate measurement of particle size distribution of emulsions with high concentration.

关键词： extended coupled phase model sound attenuation high concentration emulsion differential evolution algorithm

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A channel allocation method based on dual-population differential evolution in wireless sensor networks

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INTERNATIONAL JOURNAL OF SENSOR NETWORKS 2021年第1期36卷 50-58页

作者： Cao, Yu Wei, N. A. Pei, Huiting Jiangsu Second Normal Univ Sch Math & Informat Technol Nanjing 210013 Peoples R China Nanjing Univ Sci & Technol Sch Comp ZIJIN Coll Nanjing 210000 Peoples R China

To solve the problem of low-efficiency channel allocation due to the high density of nodes in traditional wireless sensor networks (WSNs), a channel allocation method based on dual-population differential evolution is proposed. In our paper, the crossover and mutation operations of the differential evolution algorithm are analysed;multichannel mutation crossover optimisation is proposed by combining a differential evolution algorithm with a dual-population search method. Anti-interference optimisation is carried out for different network levels with a certain capacity, considering the time slot parameter interference degree, link capacity, and multichannel cross-layer analysis. According to the multichannel mutation cross-optimisation method, the constraint conditions are determined, the channel is divided, and a linear membership function is constructed to perform channel allocation. The experimental results show that when the mutation parameter and crossover probability of two-population differential evolution are 0.1 and 0.6, respectively, the channel allocation efficiency of the proposed method is the highest, and the shortest channel allocation time is 3.4 s.

关键词： differential evolution algorithm double population cross-layer algorithm interference degree network channel allocation WSNs wireless sensor networks anti-interference optimisation

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Performance analysis of the temperature-upgraded flash-driven low-temperature advanced natural circulation heating reactor system

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NUCLEAR ENGINEERING AND DESIGN 2024年 428卷

作者： Zhang, Junxiao Su, Meiyi Chen, Ruiyang Zhou, Lunan Zhang, Chenyao He, Yu Ding, Ming Harbin Engn Univ Coll Nucl Sci & Technol Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Heilongjiang Prov Key Lab Nucl Power Syst & Equipm Harbin 150001 Peoples R China

To address the current deficiencies in outlet temperature and thermal power of low-temperature heating reactors while ensuring safety and economic viability, this study introduces the Temperature-Upgraded Flash-driven Lowtemperature Advanced Natural Circulation Heating Reactor (TU-FLANC). The FLANC system innovatively utilizes the flashing phenomenon of the coolant in the rising channel to significantly increase the coolant circulation flow rate and thus enhance thermal power at atmospheric pressure. The TU system employs an Absorption Heat Pump (AHP) to upgrade the temperature of the reactor's output heat. The two systems are interconnected via a Coupled System Heat Exchanger (CSHEX), achieving an upgrade in reactor thermal power and outlet temperature at atmospheric pressure. To evaluate the performance of the TU-FLANC system, a mathematical model of the system was established, and a computational program was developed. The impact of key parameters such as evaporator temperature, condenser temperature, and solution concentration on system performance was analyzed. The results indicate that the evaporator temperature and solution concentration have the most significant impact on the system's coefficient of performance (COP) and the coefficient of performance considering pump work (COPW). Through differential evolution (DE) algorithm optimization, the optimal solution concentration combinations were determined to maximize COP and COPW under different temperature upgrade demands. For a temperature upgrade demand of 50 degrees C, the optimal solution concentration combinations are 40.02 % and 57.48 %, with corresponding COP and COPW values of 0.5282 and 0.4886, respectively. The research findings highlight the significant innovative potential of the TU-FLANC system in enhancing heat power and outlet temperature.

关键词： TU-FLANC Flashing phenomenon Absorption heat pump COP differential evolution algorithm

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