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Scheduling Semiconductor Wafer Fabrication Using a New harmony search algorithm Based on Receipt Priority Interval

Chinese Journal of Electronics 2016年第5期25卷 866-872页

作者： ZHANG Long LIU Min HAO Jinghua WANG Xionghai DONG Jun College of Electrical Engineering Zhejiang University Department of Automation Tsinghua University

For the scheduling problem of Semiconductor wafer fabrication(SWF), a new Dispatching rule based on the load balance(DRLB) is proposed. Further, a new harmony search(HS) algorithm based receipt priority interval(HS rpi) is presented to minimize the mean cycle time. A kind of chaotic sequence is used as the harmony vector. Then, a conversion method is designed to convert the real number harmony vector to the mixed vector representing the priorities of all receipts and the algorithm parameters. In order to increase the algorithm robustness and decrease the scale of the scheduling problem, based on receipt priority interval and DRLB, we give a special conversion method used to convert the above mixed vector to the solution of the scheduling problem of SWF. Computational simulations based on the practical instances validate the proposed algorithm.

关键词： Semiconductor wafer fabrication harmony search algorithm Receipt priority interval Mean cycle time

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A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints

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APPLIED ENERGY 2016年 183卷 791-804页

作者： Zhang, Jingrui Wu, Yihong Guo, Yiran Wang, Bo Wang, Hengyue Liu, Houde Xiamen Univ Dept Instrumental & Elect Engn Xiamen Peoples R China Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equip Xian Peoples R China Univ Manchester Sch Elect & Elect Engn Manchester Lancs England Tsinghua Univ Shen Zhen Grad Sch Shenzhen Peoples R China

With constructions of demonstrative microgrids, the realistic optimal economic dispatch and energy management system are required eagerly. However, most current works usually give some simplifications on the modeling of microgrids. This paper presents an optimal day-ahead scheduling model for a microgrid system with photovoltaic cells, wind turbine units, diesel generators and battery storage systems. The power flow constraints are introduced into the scheduling model in order to show some necessary properties in the low voltage distribution network of microgrids. Besides a hybrid harmony search algorithm with differential evolution (HSDE) approach to the optimization problem is proposed. Some improvements such as the dynamic F and CR, the improved mutation, the additional competition and the discrete difference operation have been integrated into the proposed algorithm in order to obtain the competitive results efficiently. The numerical results for several test microgrids adopting the IEEE 9-bus, IEEE 39-bus and IEEE 57-bus systems to represent their transmission networks are employed to show the effectiveness and validity of the proposed model and algorithm. Not only the normal operation mode but also some typical fault modes are used to verify the proposed approach and the simulations show the competitiveness of the HSDE algorithm. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Microgrid Day-ahead scheduling Power flow harmony search algorithm Differential evolution

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Feature selection method based on multi-fractal dimension and harmony search algorithm and its application

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2016年第14期47卷 3476-3486页

作者： Zhang, Chen Ni, Zhiwei Ni, Liping Tang, Na Hefei Univ Technol Sch Management Hefei Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei Peoples R China

Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.

关键词： feature selection multi-fractal dimension harmony search algorithm fine particles (PM2.5)

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A unified methodology for single- and multiobjective in-core fuel management optimisation based on augmented Chebyshev scalarisation and a harmony search algorithm

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ANNALS OF NUCLEAR ENERGY 2016年第Part2期87卷 659-670页

作者： Schluenz, E. B. Bokov, P. M. Prinsloo, R. H. van Vuuren, J. H. South African Nucl Energy Corp SOC Ltd Radiat & Reactor Theory ZA-0001 Pretoria South Africa Univ Stellenbosch Dept Logist ZA-7602 Matieland South Africa Univ Stellenbosch Dept Ind Engn ZA-7602 Matieland South Africa

The in-core fuel management optimisation (ICFMO) problem is the problem of finding an optimal fuel reload configuration for a nuclear reactor core. ICFMO may involve the pursuit of a single or multiple objectives, while satisfying several constraints. Very little multiobjective ICFMO research involving the fundamental notion of Pareto optimality has, however, been performed. In this paper, a unified methodology is proposed for the modelling and solution of single- and multiobjective ICFMO problems, be they constrained or unconstrained. With this methodology, ICFMO problems incorporating a variety of objectives and/or constraints may be modelled and solved rapidly, thus providing a cycle-to-cycle optimisation decision support capability for nuclear reactors. An augmented Chebyshev scalarising objective function is incorporated in the methodology for modelling any number of objectives, while an additive penalty function handles potential constraints. Furthermore, an adapted harmony search algorithm is used to solve a given ICFMO problem. The algorithm is able to yield a single solution or a nondominated set of solutions as result (depending on the number of objectives in a problem). The applicability of the methodology is demonstrated by solving (approximately) a variety of ICFMO test problems for the SAFARI-I nuclear research reactor. The results indicate that the methodology may be used as an effective decision support tool for reactor operators tasked with designing reload configurations from cycle to cycle. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： In-core fuel management optimisation Multiobjective optimisation harmony search algorithm Augmented Chebyshev function Nuclear reactor

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Tournament-based harmony search algorithm for non-convex economic load dispatch problem

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APPLIED SOFT COMPUTING 2016年第0期47卷 449-459页

作者： Al-Betar, Mohammed Azmi Awadallah, Mohammed A. Khader, Ahamad Tajudin Bolaji, Asaju La'aro Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol POB 50 Irbid Jordan Al Aqsa Univ Dept Comp Sci POB 4051 Gaza Israel Univ Sains Malaysia Sch Comp Sci George Town Malaysia Fed Univ Wukari Fac Pure & Appl Sci Dept Comp Sci PMB 1029 Wukari Taraba State Nigeria

This paper proposes a tournament-based harmony search (THS) algorithm for economic load dispatch (ELD) problem. The THS is an efficient modified version of the harmony search (HS) algorithm where the random selection process in the memory consideration operator is replaced by the tournament selection process to activate the natural selection of the survival-of-the-fittest principle and thus improve the convergence properties of HS. The performance THS is evaluated with ELD problem using five different test systems: 3-units generator system;two versions of 13-units generator system;40-units generator system;and large-scaled 80-units generator system. The effect of tournament size (t) on the performance of THS is studied. A comparative evaluation between THS and other existing methods reported in the literature are carried out. The simulation results show that the THS algorithm is capable of achieving better quality solutions than many of the well-popular optimization methods. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Economic load dispatch harmony search algorithm Tournament selection Power systems Global optimization

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Quasi oppositional harmony search algorithm based controller tuning for load frequency control of multi-source multi-area power system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年第Feb.期75卷 289-302页

作者： Shankar, G. Mukherjee, V. Indian Sch Mines Dept Elect Engn Dhanbad Jharkhand India

This paper deals with the load frequency control (LFC) study of single-area and interconnected two-area power system having diversified power sources. The two areas considered in the present study are identical. Each area is having thermal, hydro and gas based power plants. Split-shaft model of gas turbine is used in the present work as one of the diversified generating unit for the purpose of LFC study. Optimal gains of the classical controllers (like integral controller, proportional-integral controller and pro portional-integral-derivative (PID) controller, one installed at a time in the studied models) are obtained by using a novel music-inspired metaheuristic harmony search algorithm (HSA) which incorporates quasi opposition based learning technique for memory initialization and also for generation jumping. Single-area power system with diverse power sources is considered and its optimal transient performances are obtained and compared for step load perturbation. The same approach is further extended to two-area interconnected power system consisting of diverse power sources with nominal values of area input parameters. The performance of PID controller is found to be the best one for the studied power system models. It is also revealed that the performance of the interconnected two-area power system with AC-DC tie line is better in comparison to AC tie line. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： AC-DC tie lines harmony search algorithm Load frequency control Multi-source power system Quasi opposition learning

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A differential-based harmony search algorithm for the optimization of continuous problems

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 62卷 317-332页

作者： Abedinpourshotorban, Hosein Hasan, Shafaatunnur Shamsuddin, Siti Mariyam As'Sahra, Nur Fatimah Univ Teknol Malaysia UTM Big Data Ctr Ibnu Sina Inst Sci & Ind Res Skudai 813W Johor Malaysia Univ Teknol Malaysia Fac Comp Skudai 813W Johor Malaysia

The performance of the harmony search (HS) algorithm is highly dependent on the parameter settings and the initialization of the harmony Memory (HM). To address these issues, this paper presents a new variant of the HS algorithm, which is called the DH/best algorithm, for the optimization of globally continuous problems. The proposed DH/best algorithm introduces a new improvisation method that differs from the conventional HS in two respects. First, the random initialization of the HM is replaced with a new method that effectively initializes the harmonies and reduces randomness. Second, the conventional pitch adjustment method is replaced by a new pitch adjustment method that is inspired by a Differential Evolution (DE) mutation strategy known as DE/best/1. Two sets of experiments are performed to evaluate the proposed algorithm. In the first experiment, the DH/best algorithm is compared with other variants of HS based on 12 optimization functions. In the second experiment, the complete CEC2014 problem set is used to compare the performance of the DH/best algorithm with six well-known optimization algorithms from different families. The experimental results demonstrate the superiority of the proposed algorithm in convergence, precision, and robustness. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： harmony search algorithm Continuous optimization Evolutionary optimization Differential evolution Meta-heuristics

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Performance Study of harmony search algorithm for Multilevel Thresholding

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JOURNAL OF INTELLIGENT SYSTEMS 2016年第4期25卷 473-513页

作者： Ouadfel, Salima Taleb-Ahmed, Abdelmalik Constantine 2 Univ Coll Engn Dept Comp Sci Constantine 25000 Algeria Univ Valenciennes & Hainaut Cambresis Lab Ind & Human Automat Mech & Comp Sci LAMIH CNRSUVHCUMR 8201 F-59313 Le Mt Houy 9 Valenciennes France

Thresholding is the easiest method for image segmentation. Bi-level thresholding is used to create binary images, while multilevel thresholding determines multiple thresholds, which divide the pixels into multiple regions. Most of the bi-level thresholding methods are easily extendable to multilevel thresholding. However, the computational time will increase with the increase in the number of thresholds. To solve this problem, many researchers have used different bio-inspired metaheuristics to handle the multilevel thresholding problem. In this paper, optimal thresholds for multilevel thresholding in an image are selected by maximizing three criteria: Between-class variance, Kapur and Tsallis entropy using harmony search (HS) algorithm. The HS algorithm is an evolutionary algorithm inspired from the individual improvisation process of the musicians in order to get a better harmony in jazz music. The proposed algorithm has been tested on a standard set of images from the Berkeley Segmentation Dataset. The results are then compared with that of genetic algorithm (GA), particle swarm optimization (PSO), bacterial foraging optimization (BFO), and artificial bee colony algorithm (ABC). Results have been analyzed both qualitatively and quantitatively using the fitness value and the two popular performance measures: SSIM and FSIM indices. Experimental results have validated the efficiency of the HS algorithm and its robustness against GA, PSO, and BFO algorithms. Comparison with the well-known metaheuristic ABC algorithm indicates the equal performance for all images when the number of thresholds M is equal to two, three, four, and five. Furthermore, ABC has shown to be the most stable when the dimension of the problem is too high.

关键词： Image segmentation multilevel thresholding harmony search algorithm optimization metaheuristics

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Fuzzy harmony search algorithm based optimal power flow for power system security enhancement

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年第Jun.期78卷 72-79页

作者： Pandiarajan, K. Babulal, C. K. Pandian Saraswathi Yadav Engn Coll Dept Elect & Elect Engn Arasanoor India Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai Tamil Nadu India

This paper proposes the integration of fuzzy logic system with harmony search algorithm (FHSA) to find the optimal solution for optimal power flow (OPF) problem in a power system. The objective of the method is to minimize the total fuel cost of thermal generating units having quadratic cost characteristics and severity index (SI). The generator active power, generator bus voltage magnitude, transformer taps, VAR of shunts and the reactance of thyristor controlled series capacitor (TCSC) are taken as the control variables. The adjustment of proposed algorithm parameters such as pitch adjustment rate (PAR) and bandwidth (BW) is done through fuzzy logic system (FLS). The effectiveness of the proposed method has been tested on the standard IEEE 30 bus, IEEE 57 bus and IEEE 118 bus systems in MATLAB environment and their results are compared with conventional harmony search algorithm (HSA) and other heuristic methods reported in the literature recently. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Optimal power flow harmony search algorithm Fuzzy logic system Optimization Power systems

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Topology optimization of double and triple layer grid structures using a modified gravitational harmony search algorithm with efficient member grouping strategy

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COMPUTERS & STRUCTURES 2016年 172卷 40-58页

作者： Mashayekhi, Mostafa Salajegheh, Eysa Dehghani, Milad Vali E Asr Univ Rafsanjan Dept Civil Engn Rafsanjan Iran Shahid Bahonar Univ Kerman Dept Civil Engn Kerman Iran

An efficient modified gravitational harmony search algorithm (MGHSA) for topology optimization of double and triple layer grid structures is presented in the article. In MGHSA, the best agents in each iteration are identified and each of them is considered as a group leader. Other agents are randomly located in these groups. To determine the new agents' positions, only the group leader applies force to the other agents in the group. Also, a novel member grouping strategy is included in the optimization algorithm. Optimization results demonstrate the efficiency of the novel MGHSA algorithm and member grouping strategy developed in this study. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Topology and sizing optimization of trusses Gravitational search algorithm Efficient member grouping Double and triple layer grid structures harmony search algorithm

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