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heuristic optimisation algorithm for Java dynamic compilation

IET SOFTWARE 2012年第4期6卷 307-312页

作者： Liu, Y. Fong, A. S. Guangdong Univ Technol Fac Comp Univ Mega Ctr Guangzhou 51006 Guangdong Peoples R China City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China

Dynamic compilation increases Java virtual machine (JVM) performance because running compiled codes is faster than interpreting Java bytecodes. However, inappropriate decision on dynamic compilation may degrade performance owing to compilation overhead. A good heuristic algorithm for dynamic compilation should achieve an appropriate balance between compilation overhead and performance gain in each method invocation sequence. A method-size and execution-time heuristic algorithm is proposed in the study. The key principle of the algorithm is that different method-sizes necessitate different compile thresholds for optimal performance. A parameter search mechanism using a genetic algorithm for dynamic compilation is proposed to find optimised multi-thresholds in the algorithm. This heuristic algorithm is evaluated in an openJDK Java Server JVM using SPEC JVM98 benchmark suite. The algorithm shows an overall advantage in performance speedup when testing benchmarks and gain speedup by 19.1% on average. The algorithm also increases the performance of original openJDK by 10.2% when extended to the whole benchmark suite.

关键词： software performance evaluation parameter search mechanism Compilers, interpreters and other processors Computer engineering Java execution-time heuristic algorithm optimisation techniques performance gain performance speedup JVM performance performance degradation SPEC JVM98 benchmark suite openJDK Java Server JVM Java virtual machine performance genetic algorithm code compilation Java dynamic compilation heuristic optimisation algorithm virtual machines benchmark testing optimal performance thresholds optimised multithresholds Software performance evaluation compilation overhead optimising compilers Object-oriented programming genetic algorithms method-size heuristic algorithm

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A novel heuristic optimisation algorithm for automated design of resonant compensators for shunt active filters

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IET POWER ELECTRONICS 2013年第9期6卷 1842-1850页

作者： Lenwari, Wanchak Okaeme, Nnamdi King Mongkuts Univ Technol Thonburi Dept Control Syst & Instrumentat Engn Bangkok 10140 Thailand

This study presents the automated control design for shunt active filters using a novel heuristic optimisation algorithm. The hybrid bacterial foraging optimisation algorithm is specifically developed for the automated optimisation of the modified resonant compensator for the compensation of all main harmonics, 5th, 7th, 11th and 13th. The compensator is based on the sinusoidal internal model principle providing excellent improvement in control accuracy and performance for harmonic signals. The compensator is implemented in a single rotating reference frame fixed to the supply voltage vector. The automated design procedure and a novel optimisation algorithm are presented in detail. Experimental results demonstrate the effectiveness of the proposed control design and the accuracy of current tracking performance.

关键词： active filters power harmonic filters heuristic optimisation algorithm resonant compensators shunt active filters automated control design hybrid bacterial foraging optimisation algorithm sinusoidal internal model principle control accuracy harmonic signals single rotating reference frame automated design procedure current tracking performance

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UMTS base station location planning: a mathematical model and heuristic optimisation algorithms

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IET COMMUNICATIONS 2007年第5期1卷 1007-1014页

作者： Yang, J. Aydin, M. E. Zhang, J. Maple, C. Center for Wireless Network Design (CWIND) Department of Computing and Information Systems University of Bedfordshire UK

Radio networks of universal mobile telecommunication system (UNITS) need accurate planning and optimisation, and many factors not seen in second generation (2G) networks must be considered. However, planning and optimisation of UMTS radio networks are often carried out with static simulations, for efficiency and to save time. To obtain a good trade-off between accuracy and computational load, link-level performance factors need to be taken into account. The authors propose a mathematical model for UMTS radio network planning taking into consideration fast power control, soft handover and pilot signal power in both uplink and downlink. optimisation strategies are investigated based on three meta-heuristics: genetic algorithm, simulated annealing (SA) and evolutionary-SA. The base station location problem is modelled as a simplified P-median problem, and parameter tuning of these meta-heuristics are presented. Extensive experimental results are used to compare the performance of different algorithms in terms of statistical measurements.

关键词： universal mobile telecommunication system genetic algorithms UMTS radio network planning fast power control evolutionary-simulated annealing 3G mobile communication soft handover scheme heuristic optimisation algorithm genetic algorithm telecommunication network planning simulated annealing simplified p-median problem pilot signal power UMTS base station location planning

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Adaptive True Proportional Navigation Guidance based on heuristic optimisation algorithms

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DEFENCE SCIENCE JOURNAL 2021年第2期71卷 271-281页

作者： Gozde, Haluk Ozden, Semih Natl Def Univ Turkish Mil Acad Dept Elect & Commun Engn Ankara Turkey

The PN-guidance (Proportional Guidance) still continues to be improved, because it is the simplest, cheapest and most reliable algorithm. One of the most important techniques to improve PN-guidance is to adapt the navigation constant depending on time. In this study, first, the entire adaptation methods for PN-guidance are classified, then the adaptation process is online achieved by using heuristic optimisation during guiding the missile. The novelty of this study is that the heuristic optimisation approach is used at the first time to update the navigation constant of PN-guidance. It is considered that having short program code, fast convergence speed and just simple algebraic computations without derivative are vital advantages of heuristic algorithms using into missile systems. In this scope, an Adaptive True-PN (ATPN) guidance algorithm is designed by optimising navigation constants varying according to the target behaviour. The results show that while the acceleration gap of the pitch axis decreases 21.8%, the acceleration gap of yaw axis reduces 39.68%. These reductions mean that while the missile guided by ATPN is maneuvering, it is exposed to less acceleration and less strain.

关键词： True proportional navigation guidance heuristic optimisation algorithm Adaptation Effective navigation constant Tactical missile

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Incorporating the effects of service quality regulation in decision-making framework of distribution companies

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第18期12卷 4172-4181页

作者： Jooshaki, Mohammad Abbaspour, Ali Fotuhi-Firuzabad, Mahmud Moeini-Aghtaie, Moein Lehtonen, Matti Sharif Univ Technol Dept Elect Engn Tehran Iran Sharif Univ Technol Energy Engn Dept Tehran Iran Aalto Univ Dept Elect Engn & Automat Espoo Finland

Incentive regulations of reliability have made a link between distribution companies' revenue and their service reliability. The companies have to decide how much to spend on various projects to provide an acceptable level of reliability while anticipation of load growth. Planners and decision makers require a comprehensive framework to optimally allocate available budgets to different plans with the highest benefits considering implementation of incentive regulation. This paper proposes a decision framework for the optimum share of expansion and reliability oriented plans in presence of reward-penalty mechanisms. A two-layer optimization model is introduced, where in the outer layer, an iterative algorithm is applied to determine the optimal set of long-term projects including Distributed Generations (DGs) installation. A heuristic optimization algorithm is employed in this layer. Considering long-term plans, in inner optimization layer, the optimal set of mid-term plans including feeder reinforcement, and preventive maintenance actions are determined using algorithms such as Branch-and-Cut and dynamic programming techniques. The model is further implemented on a test distribution network and the results are investigated through various case studies. Obtained results show the strong influence of incentive regulation on reliability indices.

关键词： power distribution economics power distribution reliability power distribution planning iterative methods optimisation combinatorial mathematics preventive maintenance decision making service quality regulation decision-making framework distribution companies incentive regulations financial link load growth optimal available budget allocation expansion plans reliability-oriented plans reward-penalty mechanisms two-layer optimisation model iterative algorithm distributed generations installation heuristic optimisation algorithm optimisation layer feeder reinforcement preventive maintenance actions mid-term plans branch-and-cut technique dynamic programming technique test distribution network reliability indices

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Waveform matching approach for fault diagnosis of a high-voltage transmission line employing harmony search algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2010年第7期4卷 801-809页

作者： Wei, L. Guo, W. Wen, F. Ledwich, G. Liao, Z. Xin, J. S China Univ Technol Sch Elect Engn Guangzhou 510640 Guangdong Peoples R China Zhejiang Univ Sch Elect Engn Hangzhou 310027 Peoples R China Queensland Univ Technol Sch Engn Syst Brisbane Qld 4001 Australia Jiangxi Elect Power Res Inst Nanchang 330006 Peoples R China

An accurate and effective technology for fault diagnosis of a high-voltage transmission line plays an important role in supporting rapid system restoration. The fault diagnosis of a high-voltage transmission line involves three major tasks, namely fault-type identification, fault location and fault time estimation. The diagnosis problem is formulated as an optimisation problem in this work: the variables involved in the fault diagnosis problem, such as the fault location, and the unknown variables such as ground resistance, are taken into account as optimisation variables;the sum of the discrepancy of the approximation components of the actual and expected waveforms is taken as the optimisation objective. Then, according to the characteristics of the formulated optimisation problem, the harmony search, an effective heuristic optimisation algorithm developed in recent years, is employed to solve this problem. Test results for a sample power system have shown that the developed fault diagnosis model and method are correct and efficient.

关键词： waveform matching approach fault time estimation high-voltage transmission line search problems fault location Inspection and quality control harmony search algorithm heuristic optimisation algorithm fault diagnosis fault-type identification optimisation power transmission lines Combinatorial mathematics rapid system restoration optimisation techniques Power transmission lines and cables

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Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model

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IET RENEWABLE POWER GENERATION 2019年第6期13卷 973-981页

作者： Li, Yang Yang, Zhen Zhao, Dongbo Lei, Hangtian Cui, Bai Li, Shaoyan Northeast Elect Power Univ Sch Elect Engn Jilin 132012 Jilin Peoples R China Argonne Natl Lab Energy Syst Div Lemont IL 60439 USA Univ Idaho Dept Elect & Comp Engn Moscow ID 83844 USA North China Elect Power Univ Sch Elect & Elect Engn Baoding 071003 Peoples R China

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment, and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides microturbine units, energy storage is employed to provide spinning reserve services for microgirds;and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimisation and decision analysis is put forward to address this model. First, a powerful heuristic optimisation algorithm, called the -dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. Thereby, the best compromise solutions are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

关键词： evolutionary computation fuzzy set theory distributed power generation Pareto optimisation power generation dispatch energy storage demand side management user experience isolated microgrid dispatch multiobjective model multiple different scheduling objectives multiobjective dynamic optimal dispatch model isolated microgrids spinning reserve services consumer satisfaction indicator dominance based evolutionary algorithm Pareto-optimal solutions energy storage microturbine units two-step solution methodology multiobjective optimisation heuristic optimisation algorithm demand side management quality of user experience evolutionary algorithm decision analysis fuzzy C-means clustering grey relation projection

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Distributed residential energy resource scheduling with renewable uncertainties

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第11期12卷 2770-2777页

作者： Luo, Fengji Dong, Zhao Yang Xu, Zhao Kong, Weicong Wang, Fan Univ Sydney Sch Civil Engn Sydney NSW 2006 Australia Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW Australia Hong Kong Polytech Univ Dept Elect Engn Hong Kong Hong Kong Peoples R China Zhejiang Univ Sch Management Hangzhou Zhejiang Peoples R China

Advances in metering and two-way communication technologies foster the studies of Home Energy Management System (HEMS). This study proposes a new HEMS, which optimally schedules the distributed residential energy resources (DRERs) in a smart home environment with varying electricity tariff and high solar penetrations. The uncertainties of solar power output are captured by using Monte Carlo sampling technique to generate multiple solar output scenarios based on the probabilistic solar radiation model. The homeowner's rigid and elastic restrictions on the operations of the automatically controlled household appliances are modelled. Based on this, an optimal DRER scheduling model is proposed to minimise the home operation cost while taking into account the homeowner's requirements. A new heuristic optimisation algorithm recently proposed by the authors, i.e. natural aggregation algorithm, is used to solve the proposed model. Simulations based on real Australian solar data are conducted to validate the proposed method.

关键词： renewable energy sources energy management systems tariffs power markets solar power stations power generation scheduling Monte Carlo methods sampling methods probability domestic appliances optimisation cost reduction distributed power generation power generation economics distributed residential energy resource scheduling renewable uncertainty two-way communication technology home energy management system HEMS smart home environment electricity tariff solar power output Monte Carlo sampling technique probabilistic solar radiation model automatically controlled household appliance optimal DRER scheduling model heuristic optimisation algorithm natural aggregation algorithm Australian solar data

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optimisation method of network level pavement maintenance planning based on benefit maximisation subject to budget constraints and a case study

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INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING 2023年第1期24卷

作者： Zhu, Haoran Huang, Jiuda Yin, Chaoen Komma, Christian Liu, Yuetong Hohai Univ Nanjing Peoples R China JSTI Grp Co Ltd Nanjing Peoples R China Nanjing Tech Univ Nanjing Peoples R China HELLER Ingn Gesell Co Ltd Darmstadt Germany

Considering that the decision-making and planning of large-scale highway network under the condition of limited funds, there are some problems such as complex algorithm of feasible solution of maintenance scheme and low efficiency of optimisation process, a heuristic maintenance planning optimisation algorithm based on budget is introduced. This paper focuses on the performance prediction, the determination of treatment measures and the optimisation of the optimal scheme. Firstly, through the analysis of the technical process of prediction and treatment measures, the pavement performance degradation models of pavement condition index, riding quality index and rut depth index based on treatment level are established. Then, based on the characteristics of pavement performance degradation in China, the concept of maintenance benefit based on pavement performance index is proposed, and the cost-benefit optimisation model of highway asphalt pavement is established. A budget-based heuristic algorithm is proposed to solve the optimisation model for maintenance planning with budget constraints. Finally, taking Lian-Xu highway network in a case study, the optimal scheme of treatment measures and fund allocation for the maintenance section of the large-scale highway network is realised under the condition of limited funds, so as to verify the feasibility of the optimisation model.

关键词： Highway pavement maintenance maintenance planning model maintenance benefit optimisation scheme heuristic optimisation algorithm

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