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A Novel Mutual Fractional Grey Bernoulli Model With differential evolution algorithm and Its Application in Education Investment Forecasting in China

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IEEE ACCESS 2020年 8卷 97839-97850页

作者： Xie, Wanli Pu, Bin Pei, Chunying Lee, Shin-Jye Kang, Yan Nanjing Normal Univ Inst EduInfo Sci & Engn Nanjing 210097 Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410006 Peoples R China Piesat Informat Technol Co Ltd Aerosp Piesat Res Inst Beijing 100048 Peoples R China Natl Chiao Tung Univ Inst Technol Management Hsinchu 30010 Taiwan Yunnan Univ Natl Pilot Sch Software Kunming 650091 Yunnan Peoples R China

Nowadays, the nonlinear grey Bernoulli model [NGBM(1,1)] has been successfully applied to various fields. Its main advantage is that the power exponent can better reflect the non-linear characteristics of the original data. However, the parameters of the model (i.e., the order of accumulation, coefficient of background value, and power index) must be optimized to fit the development law of the system. In this study, a fractional non-linear grey Bernoulli model [MFNGBM (1,1)] is proposed to reduce the perturbation limit of the classical NGBM and further improve the accuracy of the model, which uses mutual fractional operators and a new optimization scheme with a differential evolution (DE) algorithm for forecasting education investment. In the scheme, the power exponent of the Bernoulli differential equation, coefficient of background, and cumulative order of the original sequence are taken as decision variables, and their optimal parameters obtained by iteratively adjusting fitness functions. The experimental evaluation is conducted on two types of open-source data, and the results show that the proposed method can be very competitive with the popular baselines. Finally, MFNGBM(1,1) is used to predict China's education investment in 2020-2025.

关键词： Predictive models Mathematical model Investment Education Forecasting Indexes Optimization Grey system grey forecasting model non-linear grey bernoulli model fractional order differential evolution algorithm educational investment

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A novel case adaptation method based on differential evolution algorithm for disaster emergency

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APPLIED SOFT COMPUTING 2020年 92卷 106306-106306页

作者： Yu, Xiaobing Li, Chenliang Zhao, Wen-Xuan Chen, Hong Nanjing Univ Informat Sci & Technol Sch Management Sci & Engn Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Forecast & Evaluat Meteoro Nanjing 210044 Peoples R China Chang Gung Univ Grad Inst Business Management Taoyuan 333 Taiwan

When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptation is the core. To improve the adaptation, a hybrid mutation operator is implemented, and a new differential evolution (DE) algorithm is developed. An adaptation method based on the proposed algorithm is put forward to achieve case adaptation in the CBR system. The comparison results have shown that the proposed algorithm is superior compared with the state-of-art algorithms. Then, experiments of CBR have revealed that the adaptation method can effectively generate appropriate solutions with the help of the proposed algorithm. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Case-based reasoning differential evolution algorithm Disaster emergency Adaptation

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A novel modified bat algorithm hybridizing by differential evolution algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2020年 141卷 112949-000页

作者： Ylidizdan, Gulnur Baykan, Omer Kaan Selcuk Univ Kulu Vocat Sch Kulu Konya Turkey Konya Tech Univ Fac Engn & Nat Sci Dept Comp Engn Konya Turkey

The bat algorithm (BA) is one of the metaheuristic algorithms that are used to solve optimization problems. The differential evolution (DE) algorithm is also applied to optimization problems and has successful exploitation ability. In this study, an advanced modified BA (MBA) algorithm was initially proposed by making some modifications to improve the exploration and exploitation abilities of the BA. A hybrid system (MBADE), involving the use of the MBA in conjunction with the DE, was then suggested in order to further improve the exploitation potential and provide superior performance in various test problem clusters. The proposed hybrid system uses a common population, and the algorithm to be applied to the individual is selected on the basis of a probability value, which is calculated in accordance with the performance of the algorithms;thus, the probability of applying a successful algorithm is increased. The performance of the proposed method was tested on functions that have frequently been studied, such as classical benchmark functions, small-scale CEC 2005 benchmark functions, large-scale CEC 2010 benchmark functions, and CEC 2011 real-world problems. The obtained results were compared with the results obtained from the standard BA and other findings in the literature and interpreted by means of statistical tests. The developed hybrid system showed superior performance to the standard BA in all test problem sets and produced more acceptable results when compared to the published data for the existing algorithms. In addition, the contribution of the MBA and DE algorithms to the hybrid system was examined. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Heuristic algorithms Bat algorithm differential evolution algorithm Continuous optimization Large-scale optimization

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Supply allocation: bi-level programming and differential evolution algorithm for Natural Disaster Relief

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2020年第1期23卷 203-217页

作者： Chen, Ying-xin Tadikamalla, Pandu R. Shang, Jennifer Song, Yan Harbin Engn Univ Sch Econ & Management 145 Nantong St Harbin 150001 Peoples R China Univ Pittsburgh Joseph M Katz Grad Sch Business Mervis Hall Pittsburgh PA 15260 USA

Delivering relief supplies to victims of natural disasters is a very complicated process faced with many challenges: damaged road network, high demand for various materials, scarcity of resources, multi-supply and multi-demand sites, limited transport capacity, etc. Traditionally, outreach maximization is the focus of emergency relief. In this research, we propose a bi-level programming model which takes the aforementioned challenges into full account. We consider two objectives: minimizing the distribution time, and maximizing the allocation fairness. Because the problem is NP-hard, we design an improved differential evolution (IDE) algorithm and numerically compare it with several conventional differential evolution algorithms, including CoDE, SaDE, JADE and JDE. We found that the proposed IDE outperforms the existing algorithms. The feasibility and validity of the proposed model and the IDE algorithm are verified by applying them to the 2008 Wenchuan earthquake in western China.

关键词： Emergency decision-making Resource allocation bi-level programming model differential evolution algorithm Natural disaster relief

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Application of a differential evolution algorithm in the Design of Public Lighting Installations Maximizing Energy Efficiency

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LEUKOS 2020年第3期16卷 217-227页

作者： Rabaza, Ovidio Gomez-Lorente, Daniel Pozo, Antonio M. Perez-Ocon, Francisco Univ Granada Dept Civil Engn Granada Spain Univ Granada Dept Opt Granada Spain

This article presents a differential evolution (DE) algorithm that can be used to plan public lighting for streets, roadways, and freeways and maximize the energy efficiency of the installation. The algorithm was applied to a model based on new relationships between the energy efficiency of street lighting systems and geometric parameters such as street width, luminaire height, and distance between poles. These relationships were derived from the regression analysis of a large sample of outputs. The results of this algorithm consisted of the luminaire arrangement (one-sided, two-sided staggered, and two-sided coupled), luminaire height, luminaire type, and pole spacing for the most energy-efficient installation. The input of the algorithm was the lighting class or illuminance level, street width, as well as various other luminaire parameters. When these results were compared with those of DIALux, the performance of this new method was found to be extremely satisfactory. Furthermore, the constraints applied guaranteed compliance with the recommendations of the International Commission on Illumination.

关键词： differential evolution algorithm energy efficiency optimization public lighting

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Hybrid differential evolution algorithm and genetic operator for multi-trip vehicle routing problem with backhauls and heterogeneous fleet in the beverage logistics industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 146卷 106571-106571页

作者： Sethanan, Kanchana Jamrus, Thitipong Khon Kaen Univ Fac Engn Dept Ind Engn Res Unit Syst Modeling Ind Khon Kaen 40002 Thailand

Logistics is increasingly challenging because of increased competition and the uncertainty introduced by globalization. The drinks distribution system considered here uses glass bottles for soft drinks to deliver to all customers who need soft drinks in glass bottles, before making any pickups of empty glass bottles from clients to return to the company. This study aims at both an integer linear programming formulation and a novel hybrid differential evolution algorithm involving a genetic operator with fuzzy logic controller, for solving the multitrip vehicle routing problem with backhauls and a heterogeneous fleet. The objective function is to minimize total cost, which is related to distance travelled. For validation, we designed numerical experiments to compare the proposed approaches with LINGO computational software, using the conventional differential evolution algorithm and differential evolution with selected genetic operator and fuzzy logic controller in real settings. The experimental results demonstrate the practical viability of the proposed approaches.

关键词： Vehicle routing problem Backhauls Multiple trips differential evolution algorithm Genetic operator

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An Application of differential evolution algorithm-based Restricted Boltzmann Machine to Recommendation Systems

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JOURNAL OF INTERNET TECHNOLOGY 2020年第3期21卷 701-712页

作者： Kuo, R. J. Chen, J. T. Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan Chunghwa Telecom Co Ltd Dept Big Data Taipei Taiwan

Due to growth of electronic commerce, currently, many customers prefer to buying products from the internet. Thus, recommendation system, like restricted Boltzmann machine (RBM), has become a good technique to recommend the right product to the potential customer. This can dramatically increase the customer loyalty. However, it is necessary to determine some parameters for RBM and enhance its computation performance. Therefore, this study intends to propose a hybrid algorithm which combines the cluster-based restricted Boltzmann machine (CRBM) with differential evolution (DE) algorithm to optimize the RBM's parameters for collaborative filtering. The CRBM applies a clustering algorithm to determine the size and elements for each mini-batch gradient descent method for the RBM. The proposed DE-based CRBM algorithm is validated using four benchmark datasets. The results are compared with those of batch RBM, mini-batch RBM, clustering RBM, PSO-based and GA-based clustering RBM. The experimental results reveal that optimizing the RBM's parameters using metaheuristic can obtain the better result. It also show that the proposed DE-based CRBM algorithm performs better than GA-based and PSO-based CRBM algorithms.

关键词： Recommendation systems Collaborative filtering Restricted Boltzmann machine K-means algorithm differential evolution algorithm

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Production cost optimization of enzyme washing for indigo dyed cotton denim by combining Kriging surrogate with differential evolution algorithm

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TEXTILE RESEARCH JOURNAL 2020年第15-16期90卷 1860-1871页

作者： Xu, Jie He, Zhenglei Li, Sheng Ke, Wenbo Wuhan Text Univ 1 Yangguang Ave Wuhan 430200 Hubei Peoples R China Natl Local Joint Engn Lab Adv Text Proc & Clean P Wuhan Peoples R China Adv Denim Co Ltd Foshan Peoples R China

The enzyme washing process is extensively applied in the industrial production of denim garments. The process parameters of enzyme washing have significant effects on washing performances and costs. Since the relationships between the process parameters and washing performances cannot be expressed explicitly, it is impractical to determine the process parameters to obtain the optimal production cost while satisfying requirements of customers intuitively. This paper proposes an optimization methodology by combining Kriging surrogate and differential evolution (DE) algorithm to address the production cost optimization of enzyme washing for indigo dyed cotton denim. First, an experiment using Taguchi L-16 orthogonal array is conducted where temperature and concentration of cellulase enzyme are taken into consideration with processing time as the input parameters, while the washing performances (including color strength value, stiffness, and tensile strength in warp and weft directions of the washed denim fabrics) are the output responses. Second, the relationships between the inputs and outputs are established using the Kriging model. Third, the effects of the input parameters on the washing performances are analyzed, and the production cost optimization model is illustrated. Finally, a case study is given to depict the optimization process and a verification experiment is conducted to verify the effectiveness of the optimal values. On the whole, the proposed hybrid method, Kriging-DE, shows great capability of optimizing the production costs of the enzyme washing process for indigo dyed cotton denim.

关键词： enzyme washing denim production cost Kriging differential evolution algorithm

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Pattern Synthesis of Linear Antenna Array Using Improved differential evolution algorithm with SPS Framework

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SENSORS 2020年第18期20卷 5158页

作者： Zhang, Ruimeng Zhang, Yan Sun, Jinping Li, Qing Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China Univ Cambridge Dept Engn Cambridge CB1 2PZ England

In this paper, an improved differential evolution (DE) algorithm with the successful-parent-selecting (SPS) framework, named SPS-JADE, is applied to the pattern synthesis of linear antenna arrays. Here, the pattern synthesis of the linear antenna arrays is viewed as an optimization problem with excitation amplitudes being the optimization variables and attaining sidelobe suppression and null depth being the optimization objectives. For this optimization problem, an improved DE algorithm named JADE is introduced, and the SPS framework is used to solve the stagnation problem of the DE algorithm, which further improves the DE algorithm's performance. Finally, the combined SPS-JADE algorithm is verified in simulation experiments of the pattern synthesis of an antenna array, and the results are compared with those obtained by other state-of-the-art random optimization algorithms. The results demonstrate that the proposed SPS-JADE algorithm is superior to other algorithms in the pattern synthesis performance with a lower sidelobe level and a more satisfactory null depth under the constraint of beamwidth requirement.

关键词： random optimization algorithm differential evolution algorithm SPS framework SPS-JADE algorithm antenna array sidelobe suppression null depth pattern synthesis

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Mechanistic Interpretation for Xanthate Adsorption onto Galena through Electrochemical Impedance Spectrum Fitting by a differential evolution algorithm

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INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE 2020年第1期15卷 666-676页

作者： Moreno-Medrano, E. D. Osuna-Enciso, Valentin Casillas, N. Pedroza-Toscano, M. A. Gutierrez-Becerra, A. Larios-Duran, E. R. Univ Guadalajara Engn & Basic Sci Dept CUTonala Tateposco 48525 Mexico Univ Guadalajara CUCEI Chem Dept Gdl 44430 Mexico Univ Ctr UTEG Gdl 44430 Mexico Univ Guadalajara CUCEI Chem Engn Dept Gdl 44430 Mexico

This work is focused on understanding the interaction of native galena minerals and xanthate as well as their influence on the process of mineral separation by flotation and leaching techniques. To obtain basic and fundamental information about this interaction, a quantitative analysis of an electrochemical impedance study based on a mechanistic approach and the obtaining of its impedance transfer function is presented. The impedance transfer function was obtained from a three-reversible-stage mechanism, which included 19 parameters, all of which were satisfactorily obtained by fitting the impedance transfer function to previously reported experimental impedance spectra of the galena/xanthate interface in a wide polarization potential range of -0.2 to 0.5 V vs. SCE. The fitting procedure consisted of the application of a differential evolution (DE) algorithm. The description of this algorithm, its application and its advantages in the electrochemical impedance field are presented. Furthermore, a detailed discussion about the quantitative values obtained and its interpretation for galena/xanthate interactions is presented.

关键词： galena xanthate impedance adsorption mechanics differential evolution algorithm

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