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2010 Chinese Control and Decision Conference

作者： Tengfei Qiu,Gang Ju School of Energy and Environment,Southeast University,Nanjing 210096,China

A new multi-objective evolutionary algorithm,called selective migration parallel genetic algorithm(SMPGA) was presented in this paper,which designs a new migration strategy and qualification based on the adaptive *** SMPGA,a searching population and a elite population evolve at the same time;unique migration strategy and qualification are used to keep and improve the convergence and diversity of the Pareto optimal ***,according to their different purposes,the two populations adopt different crossover *** results show that SMPGA can find accurate and uniform Pareto optimal solutions on different multi-objective problems.

关键词： Multi-objective optimization parallel genetic algorithm Migration strategy and qualification Adaptive grid

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A Selective Migration parallel Multi-objective genetic algorithm

A Selective Migration Parallel Multi-objective Genetic Algor...

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The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

作者： Tengfei Qiu Gang Ju School of Energy and Environment Southeast University Nanjing 210096 China

ISBN: (纸本)9781424451814;9781424451821

A new multi-objective evolutionary algorithm, called selective migration parallel genetic algorithm (SMPGA) was presented in this paper, which designs a new migration strategy and qualification based on the adaptive grid. In SMPGA, a searching population and a elite population evolve at the same time;unique migration strategy and qualification are used to keep and improve the convergence and diversity of the Pareto optimal set. Besides, according to their different purposes, the two populations adopt different crossover strength. Simulation results show that SMPGA can find accurate and uniform Pareto optimal solutions on different multi-objective problems.

关键词： Multi-objective optimization parallel genetic algorithm Migration strategy and qualification Adaptive grid

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The two-dimensional double-entropy threshold based on the parallel genetic simulated annealing algorithms

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OPTIK 2016年第1期127卷 96-101页

作者： He, Lang Yu, Xiaxia Huang, Zhangcan Talab, Ahmed Mahgoub Ahmed Wuhan Univ Technol Sch Sci Wuhan 430070 Peoples R China

In this paper, aiming at solving the problem arising from the application of the two-dimensional entropy method in double, threshold segmentation, which is time-consuming and highly complex, the author introduces the parallel genetic simulated annealing algorithm to optimize it. Besides, the author structures parallel genetic simulated annealing algorithm to search for a two-dimensional maximum entropy value of the optimal threshold. This optimized algorithm shortens the calculation time, accelerates the speed of obtaining the optimal threshold and improves the efficiency of image segmentation. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： Two-dimensional entropy Simulated annealing parallel genetic algorithm Double threshold Image segmentation

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一种基于并行遗传算法的数据分类方法

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计算机科学 2002年第z1期29卷 148-151页

作者：蒙祖强蔡自兴孙国荣李枚毅石跃祥中南大学信息科学与工程学院长沙410083

　　1引言　　随着信息技术的高速发展和信息管理技术的广泛应用,自从九十年代以来,数据挖掘(Data Mining)已成为计算机科学中一个引人注目的新的研究方向[1].目前,数据挖掘技术在各大中型企业、电信业、商业、银行等部门中表现出极强... 详细信息

　　1引言　　随着信息技术的高速发展和信息管理技术的广泛应用,自从九十年代以来,数据挖掘(Data Mining)已成为计算机科学中一个引人注目的新的研究方向[1].目前,数据挖掘技术在各大中型企业、电信业、商业、银行等部门中表现出极强的应用潜力.……

关键词：并行遗传算法数据挖掘技术分类方法 parallel genetic algorithm Data Classification 信息管理技术计算机科学应用研究方向信息技术型企业电信业银行商业潜力

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Cell planning with capacity expansion in mobile communications: A tabu search approach

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2000年第5期49卷 1678-1691页

作者： Lee, CY Kang, HG Korea Adv Inst Sci & Technol Dept Ind Engn Taejon 305701 South Korea

Cell planning problem with capacity expansion is examined in wireless communications. The problem decides the location and capacity of each new base station to cover expanded and increased traffic demand. The objective is to minimize the cost of new base stations. The coverage by the new and existing base stations is constrained to satisfy a proper portion of traffic demands, The received signal power at the base station also has to meet the receiver sensitivity, The cell planning is formulated as an integer linear programming problem and solved by a tabu search algorithm. In the tabu search intensification by add and drop move is implemented by short-term memory embodied by two tabu lists. Diversification is designed to investigate proper capacities of new base stations and to restart the tabu search from new base station locations. Computational results show that the proposed tabu search is highly effective, A 10% cost reduction is obtained by the diversification strategies. The gap from the optimal solutions Is approximately 1 similar to 5% in problems that can be handled in appropriate time limits, The proposed tabu search also outperforms the parallel genetic algorithm, The cost reduction by the tabu search approaches 10 similar to 20% in problems with 2500 traffic demand areas (TDAs) in code division multiple access (CDMA).

关键词： AMPS CDMA cell planning cellular communication systems parallel genetic algorithm tabu search

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Stochastic production scheduling for water-oil displacement by reduced-order models generated using liquid production rates

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INTERNATIONAL JOURNAL OF OIL GAS AND COAL TECHNOLOGY 2023年第3期32卷 205-227页

作者： Roeinfard, Ehsan Assareh, Mehdi Iran Univ Sci & Technol IUST Fac Chem Petr & Gas Engn Tehran *** Iran

In this work, we show an effective approach for application of reduced order model (ROMs) constructed with proper orthogonal decomposition (POD) using liquid production rates for snapshot generation. These ROMs are used to maximise oil production while controlling associated water production. Using ROMs, we perform a parallel genetic algorithm (PGA) and consider liquid production rates as decision variables. The balanced rates are used for injection wells, based on open-flow potential and total amount of produced reservoir volume. The net present value (NPV) is selected as objective function to ensure project profitability and to penalise water production. The NPV by ROM optimisation is approached to within 98% of the NPV obtained by optimisation using the full-order model demonstrating acceptable accuracy. A synthetic model and a real field sector are used for evaluation. The optimisation runtime reduces by 55% in the synthetic model and 71% for optimisation with ROM in the sector case. [Received: April 4, 2022;Accepted: July 14, 2022]

关键词： production scheduling parallel genetic algorithm PGA reduced-order models ROMs waterflooding proper orthogonal decomposition POD

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Reconfiguration of Smart Distribution Systems With Time Varying Loads Using parallel Computing

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IEEE TRANSACTIONS ON SMART GRID 2016年第6期7卷 2713-2723页

作者： Asrari, Arash Lotfifard, Saeed Ansari, Meisam Univ Cent Florida Dept Elect Engn & Comp Sci Orlando FL 32816 USA Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Washington State Univ Energy Syst Innovat Ctr Pullman WA 99164 USA Pishgaman Niroo Isfahan Co Esfahan *** Iran

The problem of finding optimal configuration of automated/smart power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when the time varying nature of loads is taken into account. In this paper, a systematic approach is proposed to determine an optimal long-term reconfiguration schedule. To solve the optimization problem, a novel adaptive fuzzy-based parallel genetic algorithm (GA) is proposed that employs the concept of parallel computing in identifying the optimal configuration of the network. The integration of fuzzy logic into the proposed method enhances the efficiency of the parallel GA by adaptively modifying the migration rates among different processors during the optimization process. A computationally efficient graph encoding method based on Dandelion coding strategy is developed, which automatically generates radial topologies and prevents the construction of infeasible radial networks in the optimization process. In order to consider the dynamic behavior of the load and reduce the load condition scenarios over the year under study, fuzzy C-mean clustering method is utilized. Finally, the performance of the proposed method is demonstrated on a 119-bus distribution network, and is compared with that of conventional single GA and conventional parallel GA.

关键词： Dandelion encoding distribution network econfiguration parallel genetic algorithm radial structure

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Reconstruction of periodic unit cells of multimodal random particulate composites using genetic algorithms

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COMPUTATIONAL MATERIALS SCIENCE 2008年第2期42卷 352-367页

作者： Kumar, Natarajan Chennimalai Matous, Karel Geubelle, Philippe H. Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA

We develop a procedure for characterization and reconstruction of periodic unit cells of highly filled, multimodal, particulate composites. Rocpack, a particle packing software, is used to generate the solid propellant microstructures and one- and two-point probability functions are used to describe its statistical morphology. The reconstruction is carried out using a parallel Augmented Simulated Annealing algorithm with a novel mutation operator based on a mass-spring system to eliminate overlap and improve the code performance. Results from the reconstruction procedure, for four-phase random particulate composites of 40-70% packing fraction, are detailed to demonstrate the capabilities of the reconstruction model. The presented results suggest good convergence and repeatability of the optimization scheme, even for high volume fractions, and good scalability of the algorithm. (C) 2007 Elsevier B.V. All rights reserved.

关键词： microstructure reconstruction particle packing probability functions parallel genetic algorithm solid propellant

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Fast source term estimation using the PGA-NM hybrid method

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2017年 62卷 68-79页

作者： Li, Hui Zhang, Jianwen Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Beijing Univ Chem Technol Fluid Mech & Heat Transfer Lab Beijing 100029 Peoples R China

There are significant challenges related to estimating the source term of the atmospheric release. Urged on by robots in performing emergency responding tasks, a fast and accurate algorithm for this inversion problem is indispensable. Sometimes the NM simplex algorithm is efficient in the optimization problem, but sometimes the quality of convergence is unacceptable as a numerical breakdown, even for smooth and well-behaved functions. In contrast, full convergence might be seen in parallel genetic algorithms with a comparative slower convergence. In this paper we combine the PGA and the NM simplex algorithm by initializing simplex from the final individual of PGA results and obtaining the best vertex through simplex algorithm thereafter. A numerical simulation of the proposed algorithm shows noteworthy improvement of efficiency and robustness, compared with the PGA or the NM algorithm only.

关键词： Gaussian dispersion model Pasquill-Gifford dispersion model Nelder-Mead algorithm parallel genetic algorithm Inversion problem

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An effective new island model genetic algorithm for job shop scheduling problem

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COMPUTERS & OPERATIONS RESEARCH 2016年第Mar.期67卷 132-142页

作者： Kurdi, Mohamed Adnan Menderes Univ Dept Comp Engn TR-09010 Aydin Turkey

This paper presents an effective new island model genetic algorithm to solve the well-known job shop scheduling problem with the objective of minimizing the makespan. To improve the effectiveness of the classical island model genetic algorithm, we have proposed a new naturally inspired evolution model and a new naturally inspired migration selection mechanism that are capable of improving the search diversification and delaying the premature convergence. In the proposed evolution model, islands employ different evolution methods during their self-adaptation phases, rather than employing the same methods. In the proposed migration selection mechanism, worst individuals who are least adapted to their environments migrate first, hoping in finding a better chance to live in a more suitable environment that imposes a more suitable self-adaptation method on them. The proposed algorithm is tested on 52 benchmark instances, with the proposed evolution model and migration selection mechanism, and without them using the classical alternatives, and also compared with other algorithms recently reported in the literature. Computational results verify the improvements achieved by the proposed evolution model and migration selection mechanism, and show the superiority of the proposed algorithm over the others in terms of effectiveness. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Job shop scheduling Island model parallel genetic algorithm Evolutionary computation

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