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IEEE International Conference on Computing, Communication and Automation (ICCCA)

作者： Choudhary, Nikky Sharma, Harish Sharma, Nirmala Rajasthan Tech Univ Kota India

ISBN: (纸本)9781509016662

differential evolution (DE) algorithm is a population-based meta-heuristic for solving various complex optimization problems. Mutation scale factor and Crossover constant are the two important control parameters of the algorithm which are used to direct the search process to the global optima. Fine tuning of both the parameters controls the performance of the algorithm. Literature suggests that due to large step sizes, DE is unable to exploit the promising search space. So, to improve exploitation capability of the algorithm, by taking inspiration from levy flight random walk, a new mutation scale factor, namely stochastic mutation factor is proposed and incorporated with DE. The proposed strategy is named as differential evolution algorithm using Stochastic Mutation (DESMU). Further, to increase the exploration capability of the algorithm, a limit is associated with every solution to count the number of not updating iterations. If this count crosses the pre-defined limit then the solution is randomly initialized. The proposed algorithm is tested over 15 benchmark test functions and compared with basic (DE), and two of its variants namely Scale Factor Local Search differential evolution (SFLSDE) and Self-adaptive differential evolution (SADE). The results reveal that DESMU is a competitive variant of DE.

关键词： differential evolution algorithm Optimization Levy Flight Nature Inspired algorithms

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differential evolution algorithm for Solving Coil Scheduling Problem in Parallel Continuous Annealing Lines 28

Differential Evolution Algorithm for Solving Coil Scheduling...

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28th Chinese Control and Decision Conference

作者： Zhao, Shengnan Yang, Yang Northeastern Univ Inst Ind Engn & Logist Optimizat Shenyang 100819 Peoples R China

ISBN: (纸本)9781467397148

This paper studies the coil scheduling problem in parallel continuous annealing lines, which is derived from practical steel production. The problem is to assign the candidate coils to the parallel continuous annealing lines, and make the schedule of the coils in each production line, aiming at reducing the total changeover cost, and improving the production capacity utilization. To solve the problem, a new differential evolution (Sa-PDDE) algorithm is proposed with consideration of the practical production restrictions. Finally, the efficiency of the proposed algorithm is verified by computational experiments.

关键词： Scheduling differential evolution algorithm Continuous annealing

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Modeling and optimization of CNC milling of AISI 1050 steel by a regression based differential evolution algorithm (DEA)

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MATERIALS TESTING 2016年第7-8期58卷 632-639页

作者： Esme, Ugur Kulekci, Mustafa Kemal Ustun, Deniz Buldum, Baris Kazancoglu, Yigit Ocalir, Seref Mersin Univ Tarsus Fac Technol Dept Automot Engn Tarsus Mersin Turkey Mersin Univ Dept Mech Engn Tarsus Mersin Turkey Mersin Univ Adv Technol Educ Res & Applicat Ctr Tarsus Mersin Turkey Izmir Univ Econ Dept Business Adm Izmir Turkey Mersin Univ Grad Sch Nat & Appl Sci Tarsus Mersin Turkey

The present study is aimed at finding an optimization strategy for the CNC pocket milling process based on regression analysis including differential evolution algorithm (DEA). Milling parameters such as cutting speed, feed rate and depth of cut have been designed using rotatable central composite design (CCD). The AISI 1050 medium carbon steel has been machined by a high speed steel (HSS) flat end cutter tool with 8 mm diameter using the zig-zag cutting path strategy under air flow condition. The influence of milling parameters has been examined. The model for the surface roughness, as a function of milling parameters, has been obtained using the response surface methodology (RSM). Also, the power and adequacy of the quadratic mathematical model have been proved by analysis of variance (ANOVA) method. Finally, the process design parameters have been optimized based on surface roughness using bio-inspired optimization algorithm, called differential evolution algorithm (DEA). The enhanced method proposed in this study can be readily applied to different metal cutting processes with greater and faster reliability.

关键词： CNC milling response surface methodology differential evolution algorithm optimization

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Modified differential evolution algorithm for simple assembly line balancing with a limit on the number of machine types

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ENGINEERING OPTIMIZATION 2016年第2期48卷 253-271页

作者： Pitakaso, Rapeepan Sethanan, Kanchana Ubon Ratchathani Univ Dept Ind Engn Res Unit Syst Modelling Ind Ubon Ratchathani Thailand Khon Kaen Univ Fac Engn Res Unit Syst Modelling Ind Dept Ind Engn Khon Kaen Thailand

This article proposes the differential evolution algorithm (DE) and the modified differential evolution algorithm (DE-C) to solve a simple assembly line balancing problem type 1 (SALBP-1) and SALBP-1 when the maximum number of machine types in a workstation is considered (SALBP-1M). The proposed algorithms are tested and compared with existing effective heuristics using various sets of test instances found in the literature. The computational results show that the proposed heuristics is one of the best methods, compared with the other approaches.

关键词： simple assembly line balancing differential evolution algorithm binomial recombination exponential recombination

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System identification using Hammerstein model optimized with differential evolution algorithm

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2016年第12期70卷 1667-1675页

作者： Mete, Selcuk Ozer, Saban Zorlu, Hasan Erciyes Univ Dept Elect Elect Engn TR-38039 Kayseri Turkey

This paper aims to improve Hammerstein model for system identification area. Hammerstein model block structure is formed by cascade of linear and nonlinear parts. In literature, memoryless polynomial nonlinear (MPN) model for nonlinear part and finite impulse response (FIR) model or infinite impulse response (IIR) model for linear part are mostly preferred for Hammerstein models. In this study, a Hammerstein model is presented which is obtained by cascade form of a nonlinear second order volterra (SOV) and a linear FIR model. In addition, proposed Hammerstein model is optimized with differential evolution algorithm (DEA). In simulations, different types of systems are identified by proposed Hammerstein model. Also, performance of the proposed model is compared with different model performances. In conclusion it can be said that the main benefit of this study is that simulation results reveal the effectiveness and robustness of the proposed model. (C) 2016 Elsevier GmbH. All rights reserved.

关键词： System identification Hammerstein model differential evolution algorithm

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RLC circuit extraction with the differential evolution algorithm for conducted electromagnetic emission model of integrated circuits

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年第1期24卷 196-205页

作者： Basak, Muhammed Emin Kuntman, Ayten Yildiz Tech Univ Fac Naval Architecture & Maritime Istanbul Turkey Istanbul Univ Fac Engn Dept Elect & Elect Engn Istanbul Turkey

This paper examines the modeling of conducted electromagnetic emissions of integrated circuits. In this study, test circuits were designed and printed circuit boards were prepared to measure the input impedance at the power supply pin of the microcontroller. After S-parameter measurements of the test circuit were performed in a frequency range of 10 MHz to 2 GHz, Z-parameters were obtained via S-parameters. Next, the impedance frequency curve of the test circuit's power supply pin, which consists of a microcontroller core, printed circuit board, conductive trace, and SMA connector global impedances, was obtained. Therefore, all the traces, printed circuit board, and SMA connector impedance effects were eliminated with the deembedding technique. After all other impedance effects were deleted with the deembedding technique, the input impedance at the power supply pin of the microcontroller was obtained and shown with impedance frequency characteristics. The passive (RLC) circuit was modeled from this curve and the results were compared to the measurements. The differential evolution algorithm was used to extract the optimal RLC passive elements. Finally, sensitivity analyses were successfully performed to ensure the accuracy of the extracted circuit.

关键词： Conducted emissions electromagnetic differential evolution algorithm integrated circuits

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A differential evolution algorithm for pickups and deliveries problem with fuzzy time windows

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2016年第1期30卷 267-277页

作者： Chen, Dong Cao, Erbao Lai, Wentian Hunan Univ Coll Econ & Trade Changsha 410082 Hunan Peoples R China Hunan Prov Key Lab Logist Informat & Simulat Tech Changsha Hunan Peoples R China Yali High Sch Changsha City Changsha Hunan Peoples R China

In this paper, a pickups and deliveries problem with fuzzy time windows (PDPFTW) is presented and solved. The customer service level associated with time window is characterized by fuzzy membership functions based on fuzzy set theory. A novel multi-objective fuzzy programming model of PDPFTW is proposed. The proposed model aims at minimizing the vehicle numbers and the overall travel costs and maximizing the total customer service level. A novel differential evolution algorithm (DE) for PDPFTW is also proposed. In DE, we first adopted the novel decimal coding to construct an initial population, and then used some improved differential evolution operators unlike existing algorithm, in mutation operation, we used an integer order criterion based on natural number coding method and introduced a penalty technical to publish the infeasible solution. In addition, in the crossover operation, we designed a self-adapting crossover probability that varied with iteration. Our experimental results demonstrate the efficiency of the proposed DE, which saved some running time compare with GA in 100,200,400 and 1000 cases. At the same time, DE can get better solutions compare with GA in total distance of vehicles, total services level of customers and vehicle numbers. Moreover, we found that total service level would increase with wider time window.

关键词： differential evolution algorithm vehicle routing problem pickups and deliveries fuzzy time window

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An Improved differential evolution algorithm with Novel Mutation Strategy

An Improved Differential Evolution Algorithm with Novel Muta...

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2017 2nd International Conference on Mechatronics and Information Technology(ICMIT 2017)

作者： Xin Shen Dexuan Zou Xin Zhang School of Electrical Engineering and Automation Jiangsu Normal University

Aiming at the defects of differential evolution, such as premature convergence, low accuracy and other shortcomings, an improved differential evolution algorithm with novel mutation strategy(NMSIDE) is presented. The novel mutation strategy is used to avoid being trapped into local minima for NMSIDE. If the evolution of the individual stagnates, the individual will rely on the current best individual to move closer to the global best individual. The mutation rate varies dynamically within the range of values, and the crossover rate is dynamically varied based on the number of iterations. NMSIDE is tested on 11 standard functions and compared with the other state-of-the-art algorithms. The experimental results show that NMSIDE has higher convergence precision, faster convergence speed and better robustness.

关键词： differential evolution algorithm fitness value trapped solutions dynamic adjustment

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A self-adaptive binary differential evolution algorithm for large scale binary optimization problems

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INFORMATION SCIENCES 2016年 367卷 487-511页

作者： Banitalebi, Akbar Abd Aziz, Mohd Ismail Aziz, Zainal Abdul Univ Teknol Malaysia Ibnu Sina Inst Sci & Ind Res UTM Ctr Ind & Appl Math Utm Skudai 81310 Johor Malaysia

This study proposes a new self-adaptive binary variant of a differential evolution algorithm, based on measure of dissimilarity and named SabDE. It uses an adaptive mechanism for selecting how new trial solutions are generated, and a chaotic process for adapting parameter values. SabDE is compared against a number of existing state of the art algorithms, on a set of benchmark problems including high dimensional knapsack problems with up to 10,000 dimensions as well as on the 15 learning based problems of the Congress on evolutionary Computation (CEC 2015). Experimental results reveal that the proposed algorithm performs competitively and in some cases is superior to the existing algorithms. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Binary optimization Large-Scale global optimization Self-adaptation differential evolution algorithm Knapsack problem

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Effect of in-situ processing parameters on microstructure and mechanical properties of TiC particulate reinforced Al-4.5Cu alloy MMC fabricated by stir-casting technique - Optimization using grey based differential evolution algorithm

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MEASUREMENT 2016年 93卷 397-408页

作者： Das, Biswajit Roy, Susmita Rai, R. N. Saha, S. C. Majumder, Priyanko Natl Inst Technol Dept Mech Engn Jirania 799046 Tripura India Natl Inst Technol Dept Prod Engn Jirania 799046 Tripura India Natl Inst Technol Dept Math Jirania 799046 Tripura India

Fabrication of metal matrix composite materials by using the traditional casting process is a very promising task of developing near net shape products at a very low cost. Among these casting processes, the stir-casting technique has fine microstructures because of fast cooling, less porosity and good quality bonding among particle and the base matrix alloy. The major aim of this present paper is to fabricate titanium carbide reinforced metal matrix composite (MMC) by using micron sized activated charcoal powder, to get react with titanium material for producing TiC intermetallic particles in the Al-4.5%Cu matrix by in-situ technique so as to produce Al-4.5%Cu-5% TiC MMC, with the intention of finding the optimum processing parameter i.e. pouring temperature, stirring speed in liquid melt-stirring process, reaction time with the aim of achieving better microstructure and mechanical properties, i.e. micro-hardness, toughness and ultimate tensile strength by using an efficient grey based differential evolution algorithm. Mechanical properties of optimum processing condition are verified by doing confirmation tests. ANOVA analysis is performed to analyze the role of each factor on multiple performance characteristics and it was found that stirrer rotational speed and reaction time is playing a key role in affecting the mechanical property. Additionally, to predict the response parameters regression equations were developed and the validity of regression model is tested by plotting scatter diagram. Finally microstructure study has been performed for the optimal sample by using optical microscope. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Stir casting technique MMC Microstructure Mechanical properties differential evolution algorithm

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