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A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第4期54卷 1039-1060页

作者： Zhao, Fuqing Shao, Zhongshi Wang, Junbiao Zhang, Chuck Lanzhou Univ Technol Sch Comp & Commun Technol Lanzhou Peoples R China Northwestern Polytech Univ Key Lab Contemporary Design & Integrated Mfg Tech Minist Educ Xian 710072 Peoples R China Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA

Job shop scheduling problem (JSSP) is a typical NP-hard problem. In order to improve the solving efficiency for JSSP, a hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search is proposed in this paper, which combines the merits of Estimation of distribution algorithm and differential evolution (DE). Meanwhile, to strengthen the searching ability of the proposed algorithm, a chaotic strategy is introduced to update the parameters of DE. Two mutation operators are adopted. A neighbourhood search (NS) algorithm based on blocks on critical path is used to further improve the solution quality. Finally, the parametric sensitivity of the proposed algorithm has been analysed based on the Taguchi method of design of experiment. The proposed algorithm was tested through a set of typical benchmark problems of JSSP. The results demonstrated the effectiveness of the proposed algorithm for solving JSSP.

关键词： estimation of distribution algorithm differential evolution algorithm neighbourhood search hybrid optimisation job shop scheduling

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State-of-charge estimators considering temperature effect, hysteresis potential, and thermal evolution for LiFePO₄ batteries

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2018年第8期42卷 2710-2727页

作者： Xie, Jiale Ma, Jiachen Bai, Kun Harbin Inst Technol Sch Astronaut Harbin Heilongjiang Peoples R China State Grid Jibei Elect Power Co Ltd Maintenance Branch Beijing Peoples R China

To achieve accurate state-of-charge (SoC) estimation for LiFePO4 batteries, the effects of temperature, hysteresis, and thermal evolution are elaborately modeled. Open-circuit voltage is regarded as the sum of electromotive force and hysteresis potential (="mathematics"V-h), where electromotive force is constructed as the function of SoC and temperature and ="mathematics">V-h is reproduced with a geometrical model. By simulating battery heat generation and dissipation, a thermal evolution model is established and exploited for open-circuit voltage and parameter identification. Then, on the basis of a second-order equivalent circuit model, 2 SoC estimation schemes are proposed: One scheme uses the recursive least square with forgetting factor algorithm and off-line equivalent circuit model parameters derived by the differential evolution algorithm;the other scheme resorts to the adaptive extended Kalman filter (EKF) and online tuned parameters. Experiments validate the effectiveness of the hysteresis model and the thermal evolution model. In contrast to a joint EKF estimator, experimental results under different temperatures and initial states suggest that both the proposed estimators are superior to the joint EKF estimator. Benefiting from the online updated parameters, the adaptive EKF estimator behaves best for giving consistent SoC-tracking performance under different conditions.

关键词： adaptive extended Kalman filter differential evolution algorithm hysteresis model parameter identification state of charge thermal evolution model

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Environmental assesment of surface waters based on monitoring data and neuro-evolutive modelling

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2018年 120卷 136-145页

作者： Dragoi, E. N. Kovacs, Zs. Juzsakova, T. Curteanu, S. Cretescu, I. Gheorghe Asachi Tech Univ Iasi Fac Chem Engn & Environm Protect 73 Blvd D Mangeron Iasi 700050 Romania Univ Pannonia Inst Environm Engn Egyet St 10 HU-8200 Veszprem Hungary

The surface water quality highly depends on the natural conditions and on the industrial, agricultural and other anthropogenic activities in the river catchment areas. The quality of the surface water is the key factor in the water quality management. The monitoring of the water quality indicators is requested to follow up (in time and space) the changes in the water quality, providing healthy water for the people. The water quality indicators (physical-chemical specific parameters such as: pH, electrical conductivity, dissolved oxygen, turbidity etc.) provide information about the pollution degree of different waters (stemming from wastewater treatment plants, precipitation, sewer lines, tributaries, etc.). The main aim of the research was to demonstrate the efficiency of artificial intelligence techniques for the water quality prediction. Consequently, the considered system was modelled using a neuro-evolutive technique, combining artificial neural networks (ANN) with differential evolution (DE) algorithm. The neural network acts as a system model, while the differential evolution algorithm is the optimizer with the function to determine the optimal parameters of the model. The simulation results pointed out that the approach is suitable to set up adequate models for the three parameters, pH, electrical conductivity, dissolved oxygen, respectively. For the fourth parameter (turbidity), an average absolute error of 30% was obtained, which indicates a more complex relation in rapport to the other parameters of the system. The DE-ANN approach can, thus, be further used in decision making solutions for water quality management. (C) 2018 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.

关键词： Water framework directive Surface water monitoring Water quality assessment Artificial neural networks differential evolution algorithm

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Improved differential evolution algorithms for solving generalized assignment problem

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 45卷 450-459页

作者： Sethanan, Kanchana Pitakaso, Rapeepan Khon Kaen Univ Fac Engn Dept Ind Engn Res Unit Syst Modeling Ind Khon Kaen 40002 Thailand Ubon Ratchathani Univ Fac Engn Dept Ind Engn Metaheurist Logist Optimizat Lab Ubon Ratchathani Thailand

This paper presents algorithms based on differential evolution (DE) to solve the generalized assignment problem (GAP) with the objective to minimize the assignment cost under the limitation of the agent capacity. Three local search techniques: shifting, exchange, and k-variable move algorithms are added to the DE algorithm in order to improve the solutions. Eight DE-based algorithms are presented, each of which uses DE with a different combination of local search techniques. The experiments are carried out using published standard instances from the literature. The best proposed algorithm using shifting and k-variable move as the local search (DE-SK) techniques was used to compare its performance with those of Bee algorithm (BEE) and Tabu search algorithm (TABU). The computational results revealed that the BEE and DE-SK are not significantly different while the DE-SK outperforms the TABU algorithm. However, even though the statistical test shows that DE-SK is not significantly different compared with the BEE algorithm, the DE-SK is able to obtain more optimal solutions (87.5%) compared to the BEE algorithm that can obtain only 12.5% optimal solutions. This is because the DE-SK is designed to enhance the search capability by improving the diversification using the DE's operators and the k-variable moves added to the DE can improve the intensification. Hence, the proposed algorithms, especially the DE-SK, can be used to solve various practical cases of GAP and other combinatorial optimization problems by enhancing the solution quality, while still maintaining fast computational time. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Generalized assignment problem differential evolution algorithm Shifting procedure Exchange procedure

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A Robust Scheduling Optimization Method for Flight Deck Operations of Aircraft Carrier With Ternary Interval Durations

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IEEE ACCESS 2018年 6卷 69918-69936页

作者： Su, Xi-Chao Han, Wei Wu, Yu Zhang, Yong Song, Jing-Yu Naval Aviat Univ Yantai 264001 Peoples R China Chongqing Univ Coll Aerosp Engn Chongqing 400044 Peoples R China China State Shipbldg Corp Syst Engn Res Inst Beijing 10094 Peoples R China

The sortie and recovery operations of the carrier-based aircraft fleet are carried out in a cyclic mode, and there are uncertainties during the flight deck operations, which is the main factor that influences the sustainability of cyclic operations. The robust scheduling problem for flight deck operations (RSPFDO) with uncertain duration is studied in this paper. First, the robust scheduling model of flight deck operations with ternary interval durations is established. In this model, the precedence and resource constraints including personnel, equipment, workstation space, and supply resource are taken into account, and the uncertain duration is modeled as a ternary interval number. Second, to make a proactive plan, serial schedule generation scheme is used to generate baseline schedules, and a robust personnel allocation scheme is designed. In terms of executing schedules, a pre-constrained scheduling policy is proposed to evaluate the ternary interval of makespan. Third, a double-population and self-adaptive differential evolution (DSDE) algorithm is presented to optimize the robust plan, which is embedded in a population-based double justification scheme, self-adaptive selection of mutation and crossover factors, and a chaotic catastrophe operator based on the scouts mode of artificial bee colony algorithm. The validity of the established model and the superiority of the DSDE algorithm are verified by simulations with mission cases and algorithm comparison. The results demonstrate that the proposed robust scheduling method can effectively improve the robustness of the flight deck operations.

关键词： Flight deck operations ternary interval number robust scheduling differential evolution algorithm

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Optimum design of cam-roller follower mechanism using a new evolutionary algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2018年第5-8期99卷 1267-1282页

作者： Hamza, Ferhat Abderazek, Hammoudi Lakhdar, Smata Ferhat, Djeddou Yildiz, Ali Riza Univ Setif 1 Inst Opt & Precis Mech Setif 19000 Algeria Appl Precis Mech Lab Setif Algeria Phys & Mech Metall Mat Lab Setif Algeria Uludag Univ Dept Automot Engn Gorukle Bursa Turkey

The optimum design of a cam mechanism is a very interesting problem in the contact mechanics today, due to the alternative industrial applications as a mechanism of precision. In this paper, a new evolutionary algorithm called modified adaptive differential evolution (MADE) is introduced for multi-objective optimization of a cam mechanism with offset translating roller follower. The optimization procedure is investigated for three objectives among them minimum congestion, maximum efficiency, and maximum strength resistance of the cam. To enhance the design quality of the mechanism in the optimization process, more geometric parameters and more design constraints are included in the problem formulation. In order to validate the developed algorithm, three engineering design problems are solved. The simulation results for the tested problems indicate the effectiveness and the robustness of the proposed algorithm compared to the various existed optimization methods. Finally, the optimal results obtained for the case study example provide very useful decisions for a cam mechanism synthesis.

关键词： Cam mechanism Roller follower Constrained optimization differential evolution algorithm

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Performance-based optimal design of tuned impact damper for seismically excited nonlinear building

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ENGINEERING STRUCTURES 2018年 160卷 314-327页

作者： Lu, Zheng Li, Kun Ouyang, Yuting Shan, Jiazeng Tongji Univ State Key Lab Disaster Reduct Civil Engn Shanghai 200092 Peoples R China Tongji Univ Res Inst Struct Engn & Disaster Reduct Shanghai 200092 Peoples R China

This paper proposes a performance-based optimal design method for a tuned impact damper system, which is composed of a solid mass in a container and is located at the top of a 20-story complex nonlinear benchmark building of the third generation. This benchmark building is a steel frame, accounting for nonlinear response via material non-linearity (bi-linear hysteresis) concentrated at the ends of moment-resisting beam-column joints, and is designed for the SAC PhaselllSteel Project. In order to illustrate the real-world implementable optimal design approach for designing an optimal tuned impact damper system attached to practical complex structures, a reduced-order data-driven physical model is developed by using the response data specifically from finite element model and the optimization-based parameter identification algorithm. The reduced-order model has been iteratively constructed to be consistent favorably with the finite element model on the aspects of both modal frequencies and mode shapes. Based on the reduced-order model, the optimal parameters of the tuned impact damper system are subsequently designed by adopting proposed performance indices and the differential evolution algorithm conveniently. The optimal vibration control effects are evaluated by using the original finite element model structure with the optimal tuned impact damper. Such optimal performance is also compared with that of the original finite element model with a conventionally designed tuned impact damper system. The results show that the optimal designed tuned impact damper system not only can significantly mitigate the peak and root mean square values of dynamic displacements, but also can reduce effectively the number of plastic hinges of the nonlinear benchmark structure compared with that with the conventional design. Furthermore, the performance-based optimal design can lead to a better robust performance of the tuned impact damper system in the cases of the main structure subje

关键词： Passive control Tuned impact damper Particle damper Reduced-order model differential evolution algorithm Performance-based optimal design

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Optimized design of tube hydroforming loading path using multi-objective differential evolution

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2017年第1-4期88卷 837-846页

作者： Ge, Yu-long Li, Xiao-xing Lang, Li-hui Ruan, Shang-wen Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China

Loading path design is one of the main factors that influence the quality of tube hydroforming processes. The conflicts between different quality indicators can be solved using multi-objective optimization evolutionary algorithms. In this paper, we propose a multi-objective optimization using differential evolution to obtain the optimum cooperation between the internal pressure and end feeding process. In the optimization process, several finite element simulations are performed to set up a least-squares support vector machine-based response surface model, which significantly improves the accuracy. We used a pre-bent hydroforming case study to demonstrate that this method is effective, accurate, and reliable.

关键词： Tube hydroforming Loading path design Multi-objective optimization differential evolution algorithm Least-squares support vector machine

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Competitive evolutionary algorithms for building performance database of a microwave transistor

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2018年第2期46卷 244-258页

作者： Gunes, Filiz Belen, Mehmet A. Mahouti, Peyman Yildiz Tech Univ Dept Elect & Commun Engn Istanbul Turkey Artvin Coruh Univ Dept Elect & Elect Engn Artvin Turkey

In this work, the simultaneous trade-off relations among the noise figure F, gain G(T), input V-in, and output V-out VSWRs of a microwave transistor operated at a certain (V-DS, I-DS, f) condition are obtained fast and as accurate as the corresponding analytical results using multiobjective optimization process without any need for expertise on the microwave device, circuit, and noise. Three powerful evolutionary algorithms, cuckoo search, firefly, and differential evolution, are implemented comparatively as a study case to obtain the trade-off relations of a typical low-noise amplifier transistor NE3511S02 for its operation between 9 and 17GHz at V-DS=2V and I-DS=10mA. Finally, differential evolution is found as the most successful algorithm to demonstrate the typical trade-off relations of NE3511S02. It can be concluded that these trade-off relations being obtained by using a signal and noise model of the transistor enable performance database covering all the (FFmin, G(T), V(in)1, V(out)1) quadruples with their (Z(S), Z(L)) termination pairs using solely an evolutionary optimization process. Thus, a small signal transistor can be identified by its performance database to be used in the design optimization of high-performance low-noise amplifiers with the full device capacity.

关键词： microwave transistor multiobjective optimization competitive evolutionary algorithms low-noise amplifier (LNA) cuckoo search algorithm firefly algorithm differential evolution algorithm

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Exact Closed-Form Solution for Detection Probability in Cognitive Radio Networks With Switch-and-Examine Combining Diversity

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2018年第9期67卷 8215-8222页

作者： Namdar, Mustafa Ilhan, Haci Dumlupinar Univ Dept Elect & Elect Engn TR-43100 Kutahya Turkey Yildiz Tech Univ Dept Elect Commun Engn TR-34220 Istanbul Turkey

In this study, we analyze spectrum sensing performance by investigating amplify-and-forward based cooperative relaying in underlay cognitive radio networks with switch-and-examine combining diversity technique in which the maximal ratio combining and energy detector schemes are employed at the destination. First, we derive closed-form expressions for both the probability density functions and the probability of detections (P-d) of the end-to-end signal-to-noise ratios at the output of the switch-and-examine combiner over Rayleigh fading channel. Then, the optimal detection threshold and switching threshold values with optimizing error rate (P-e) using the differential evolution algorithm are obtained. Finally, we present some numerical results through the receiver operating characteristics curves utilizing the newly derived closed-form expressions and we verify that the numerical curves precisely match with the simulation results, validating our proposed theoretical analysis.

关键词： Amplify-and-forward relay networks detection probability differential evolution algorithm Rayleigh fading channel spectrum sensing switch-and-examine combining diversity

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