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A Review of Genetic Algorithms:Principles, Procedures, and Applications in Optimization 认领 引用
1
作者 M.A.El-Shorbagy 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期138-184,共47页
This paper provides a thorough examination of Genetic Algorithms(GAs),a category of evolutionary computation methods derived from the concepts of natural selection and genetics.The main concept and operational princip... This paper provides a thorough examination of Genetic Algorithms(GAs),a category of evolutionary computation methods derived from the concepts of natural selection and genetics.The main concept and operational principle of GAs are elucidated,highlighting the evolution of populations of candidate solutions across multiple generations to get optimal or near-optimal solutions for complicated problems.The paper delineates the sequential phases of a conventional GA,encompassing problem formulation,solution encoding,initialization of population,fitness evaluation,selection,crossover,mutation,and termination criteria,so offering a coherent framework for comprehending the algorithm’s functionality.Moreover,numerous prominent genetic operators,including crossover and mutation,are examined,highlighting their distinct forms and processes for fostering diversity and exploration within the search space.Also,the paper emphasizes the benefits of GAs,including their capacity to address nonlinear,multimodal,and high-dimensional optimization challenges without necessitating gradient information,along with their adaptability in resolving both continuous and discrete issues.The limitations and constraints of GAs,such as computing expense,parameter optimization,and the risk of premature convergence,are thoroughly analyzed.The paper examines various applications of GAs across fields,including engineering design,control systems,combinatorial optimization,machine learning,operations research,and multi-objective optimization,demonstrating the versatility and practical significance of this evolutionary method.This work establishes a robust basis for scholars and practitioners seeking to implement GAs in intricate optimization challenges.The review indicates that GAs have greatly progressed from Holland’s original formulation to specialized variations,such as real-valued,permutation,and tree-based encodings,each tailored to certain issue categories.The critical study indicates that although classical GAs are proficient in global exploration,their hybridization with local search techniques(memetic algorithms),swarm intelligence(GA-PSO),and surrogate models significantly improves convergence time and solution accuracy.The study highlights ongoing research deficiencies,such as the disparity between theoretical convergence proofs and the actual performance of algorithms,as well as the necessity for systematic recommendations in the design of hybrid algorithms. 展开更多
关键词 Genetic algorithm evolutionary computation global optimization nonlinear optimization computational intelligence optimization techniques
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A Hybrid Mashup Platform Based on Structured and Unstructured Peer-to-Peer Networks Empowered with Genetic Algorithms 认领 引用
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作者 Osama Al-Haj Hassan Ammar Odeh +1 位作者 Abdullah Aref Ghassan Samara 《Computers, Materials & Continua》 SCIE EI 2026年第9期1335-1357,共23页
Mashups are among the key web technologies that provide end-users with customizable and personalized tools.Most mashup platforms are based on centralized architectures or do not employ fully decentralized architecture... Mashups are among the key web technologies that provide end-users with customizable and personalized tools.Most mashup platforms are based on centralized architectures or do not employ fully decentralized architectures;therefore,in this paper,we propose a decentralized architecture for mashups that combines the strengths of structured and unstructured peer-to-peer networks.For the structured part,we rely on the Chord lookup protocol,and for the unstructured part,we build groups of nodes via two flavors of network flooding,namely,sequence number flooding and reverse path flooding.Brokers in the unstructured part would be responsible for hosting and executing mashups,such that deciding which brokers should host a given mashup is determined by utilizing genetic algorithms.We compare our work against several approaches that rely on random and greedy mashup placement.We also assess our proposed approach to pure structured and pure unstructured approaches.We evaluate our system using simulations,and results show that executing mashups using the version of our scheme that relies on reverse path flooding generates at least 25%lower delays than the other approaches. 展开更多
关键词 Mashup peer to peer Chord genetic algorithm
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Fuzzy Logic Based Evaluation of Hybrid Termination Criteria in the Genetic Algorithms for the Wind Farm Layout Design Problem 认领 引用
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作者 Salman A.Khan Mohamed Mohandes +2 位作者 Shafiqur Rehman Ali Al-Shaikhi Kashif Iqbal 《Computers, Materials & Continua》 SCIE EI 2025年第7期553-581,共29页
Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This ... Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This layout defines the specific locations of the turbines within the wind farm.The process of finding the optimal locations of turbines,in the presence of various technical and technological constraints,makes the wind farm layout design problem a complex optimization problem.This problem has traditionally been solved with nature-inspired algorithms with promising results.The performance and convergence of nature-inspired algorithms depend on several parameters,among which the algorithm termination criterion plays a crucial role.Timely convergence is an important aspect of efficient algorithm design because an inefficient algorithm results in wasted computational resources,unwarranted electricity consumption,and hardware stress.This study provides an in-depth analysis of several termination criteria while using the genetic algorithm as a test bench,with its application to the wind farm layout design problem while considering various wind scenarios.The performance of six termination criteria is empirically evaluated with respect to the quality of solutions produced and the execution time involved.Due to the conflicting nature of these two attributes,fuzzy logic-based multi-attribute decision-making is employed in the decision process.Results for the fuzzy decision approach indicate that among the various criteria tested,the criterion Phi achieves an improvement in the range of 2.44%to 32.93%for wind scenario 1.For scenario 2,Best-worst termination criterion performed well compared to the other criteria evaluated,with an improvement in the range of 1.2%to 9.64%.For scenario 3,Hitting bound was the best performer with an improvement of 1.16%to 20.93%. 展开更多
关键词 Wind energy wind farm layout design performance evaluation genetic algorithms fuzzy logic multi-attribute decision-making
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Interactive Genetic Algorithms with Fitness Adjustment 认领 引用 被引量：3
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作者 GUO Guang-song GONG Dun-wei HAO Guo-sheng ZHANG Yong 《Journal of China University of Mining and Technology》 2006年第4期480-484,共5页
Noises widely exist in interactive genetic algorithms. However, there is no effective method to solve this problem up to now. There are two kinds of noises, one is the noise existing in visual systems and the other is... Noises widely exist in interactive genetic algorithms. However, there is no effective method to solve this problem up to now. There are two kinds of noises, one is the noise existing in visual systems and the other is resulted from user’s preference mechanisms. Characteristics of the two noises are presented aiming at the application of interac- tive genetic algorithms in dealing with images. The evolutionary phases of interactive genetic algorithms are determined according to differences in the same individual’s fitness among different generations. Models for noises in different phases are established and the corresponding strategies for reducing noises are given. The algorithm proposed in this paper has been applied to fashion design, which is a typical example of image processing. The results show that the strategies can reduce noises in interactive genetic algorithms and improve the algorithm’s performance effectively. However, a further study is needed to solve the problem of determining the evolution phase by using suitable objective methods so as to find out an effective method to decrease noises. 展开更多
关键词 genetic algorithms interactive genetic algorithms noises strategies for reducing noises
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Research on Modified Shifting Balance Genetic Algorithms 认领 引用 被引量：1
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作者 MA Hong-mei GONG Dun-wei 《Journal of China University of Mining and Technology》 2007年第2期188-192,共5页
The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search ... The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search capability of the core population,the sub-space method was used to generate uniformly distributed initial colony populations over the decision variable space. The core population was also dynamically divided,making simultaneous searching in several local spaces possible. The algorithm proposed in this paper was compared to the original one by searching for the optimum of a complicated multi-modal function. The results indicate that the solutions obtained by the modified algorithm are better than those of the original algorithm. 展开更多
关键词 genetic algorithms shifting balance genetic algorithms small spaces dynamic partition multi-modal function
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Forward and backward models for fault diagnosis based on parallel genetic algorithms 认领 引用 被引量：10
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作者 Yi LIU Ying LI +1 位作者 Yi-jia CAO Chuang-xin GUO 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2008年第10期1420-1425,共6页
In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of faul... In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems. 展开更多
关键词 Forward and backward models Fault diagnosis Global single-population master-slave genetic algorithms （GPGAs） Parallel computation
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A comparative study of differential evolution and genetic algorithms for optimizing the design of water distribution systems 认领 引用 被引量：5
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作者 Xiao-lei DONG Sui-qing LIU +2 位作者 Tao TAO Shu-ping LI Kun-lun XIN 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2012年第9期674-686,共13页
The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performari... The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs. 展开更多
关键词 Differential evolution （DE） Genetic algorithms （GAs） Optimization Water distribution systems （WDSs）
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Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms 认领 引用 被引量：6
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作者 I.A.Chaudhry S.Mahmood M.Shami 《Journal of Central South University》 SCIE EI CAS 2011年第5期1473-1486,共14页
The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain inde... The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model. 展开更多
关键词 automated guided vehicles （AGVs） scheduling job-shop genetic algorithms flexible manufacturing system （FMS） spreadsheet
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A Hybrid Immigrants Scheme for Genetic Algorithms in Dynamic Environments 认领 引用 被引量：11
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作者 Shengxiang Yang Renato Tinós 《International Journal of Automation and computing》 2007年第3期243-254,共12页
Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the ... Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution（s） of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments. 展开更多
关键词 Genetic algorithms random immigrants elitism-based immigrants dualism dynamic optimization problems.
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Robot path planning using genetic algorithms 认领 引用 被引量：3
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作者 朴松昊 洪炳熔 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2001年第3期215-217,共3页
Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation adopted, to... Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation adopted, to avoid the common defect of early convergence and converge faster than the standard genetic algorithms concludes from simulation results that the method is effective for robot path planning. 展开更多
关键词 path planning soccer robot genetic algorithms
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DENSE DISPARITY MAP ESTIMATION USING GENETIC ALGORITHMS 认领 引用 被引量：2
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作者 王彪 沈春林 《Transactions of Nanjing University of Aeronautics and Astronautics》 2003年第2期184-191,共8页
An approach to addressing the stereo correspondence problem is presented using genetic algorithms (GAs) to obtain a dense disparity map. Different from previous methods, this approach casts the stereo matching as a mu... An approach to addressing the stereo correspondence problem is presented using genetic algorithms (GAs) to obtain a dense disparity map. Different from previous methods, this approach casts the stereo matching as a multi-extrema optimization problem such that finding the fittest solution from a set of potential disparity maps. Among a wide variety of optimization techniques, GAs are proven to be potentially effective methods for the global optimization problems with large search space. With this idea, each disparity map is viewed as an individual and the disparity values are encoded as chromosomes, so each individual has lots of chromosomes in the approach. Then, several matching constraints are formulated into an objective function, and GAs are used to search the global optimal solution for the problem. Furthermore, the coarse-to-fine strategy has been embedded in the approach so as to reduce the matching ambiguity and the time consumption. Finally, experimental results on synthetic and real images show the performance of the work. 展开更多
关键词 stereo correspondence disparity map genetic algorithms coarse-to-fine strategy
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Job-shop Scheduling with Multi-objectives Based on Genetic Algorithms 认领 引用 被引量：1
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作者 周亚勤 李蓓智 陈革 《Journal of Donghua University(English Edition)》 EI CAS 2003年第3期57-62,共6页
The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special... The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special class of NP-hard problems. Most of the algorithms used to optimize this class of problems have an exponential time; that is, the computation time increases exponentially with problem size. In scheduling study, makespan is often considered as the main objective. In this paper, makespan, the due date request of the key jobs, the availability of the key machine, the average wait-time of the jobs, and the similarities between the jobs and so on are taken into account based on the application of mechanical engineering. The job shop scheduling problem with multi-objectives is analyzed and studied by using genetic algorithms based on the mechanics of genetics and natural selection. In this research, the tactics of the coding and decoding and the design of the genetic operators, along with the description of the mathematic model of the multi-objective functions, are presented. Finally an illu-strative example is given to testify the validity of this algorithm. 展开更多
关键词 job shop scheduling multi-objective optimization genetic algorithms
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APPROXIMATION TECHNIQUES FOR APPLICATION OF GENETIC ALGORITHMS TO STRUCTURAL OPTIMIZATION 认领 引用 被引量：1
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作者 金海波 丁运亮 《Transactions of Nanjing University of Aeronautics and Astronautics》 2003年第2期147-154,共8页
Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex str... Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model. 展开更多
关键词 approximation techniques segment approximation model genetic algorithms structural optimization sensitivity analysis
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Surrogate model-assisted interactive genetic algorithms with individual’s fuzzy and stochastic fitness 认领 引用 被引量：1
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作者 Xiaoyan SUN Dunwei GONG 《控制理论与应用（英文版）》 2010年第2期189-199,共11页
We propose a surrogate model-assisted algorithm by using a directed fuzzy graph to extract a user’s cognition on evaluated individuals in order to alleviate user fatigue in interactive genetic algorithms with an indi... We propose a surrogate model-assisted algorithm by using a directed fuzzy graph to extract a user’s cognition on evaluated individuals in order to alleviate user fatigue in interactive genetic algorithms with an individual’s fuzzy and stochastic fitness.We firstly present an approach to construct a directed fuzzy graph of an evolutionary population according to individuals’dominance relations,cut-set levels and interval dominance probabilities,and then calculate an individual’s crisp fitness based on the out-degree and in-degree of the fuzzy graph.The approach to obtain training data is achieved using the fuzzy entropy of the evolutionary system to guarantee the credibilities of the samples which are used to train the surrogate model.We adopt a support vector regression machine as the surrogate model and train it using the sampled individuals and their crisp fitness.Then the surrogate model is optimized using the traditional genetic algorithm for some generations,and some good individuals are submitted to the user for the subsequent evolutions so as to guide and accelerate the evolution.Finally,we quantitatively analyze the performance of the presented algorithm in alleviating user fatigue and increasing more opportunities to find the satisfactory individuals,and also apply our algorithm to a fashion evolutionary design system to demonstrate its efficiency. 展开更多
关键词 Interactive genetic algorithms User fatigue Surrogate model Directed fuzzy graph Fuzzy entropy
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Research on the fully fuzzy time-cost trade-off based on genetic algorithms 认领 引用 被引量：1
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作者 JIN Chao-guang JI Zhuo-shang +2 位作者 LIN Yan ZHAO Yuan-min HUANG Zhen-dong 《Journal of Marine Science and Application》 2005年第3期18-23,共6页
It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect ... It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms (GAs). In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling. 展开更多
关键词 fuzzy sets ranking fuzzy number genetic algorithms time-cost trade-off
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Parallel Optimization of Program Instructions Using Genetic Algorithms 认领 引用
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作者 Petre Anghelescu 《Computers, Materials & Continua》 SCIE EI 2021年第6期3293-3310,共18页
This paper describes an efficient solution to parallelize softwareprogram instructions, regardless of the programming language in which theyare written. We solve the problem of the optimal distribution of a set ofinst... This paper describes an efficient solution to parallelize softwareprogram instructions, regardless of the programming language in which theyare written. We solve the problem of the optimal distribution of a set ofinstructions on available processors. We propose a genetic algorithm to parallelize computations, using evolution to search the solution space. The stagesof our proposed genetic algorithm are: The choice of the initial populationand its representation in chromosomes, the crossover, and the mutation operations customized to the problem being dealt with. In this paper, geneticalgorithms are applied to the entire search space of the parallelization ofthe program instructions problem. This problem is NP-complete, so thereare no polynomial algorithms that can scan the solution space and solve theproblem. The genetic algorithm-based method is general and it is simple andefficient to implement because it can be scaled to a larger or smaller number ofinstructions that must be parallelized. The parallelization technique proposedin this paper was developed in the C# programming language, and our resultsconfirm the effectiveness of our parallelization method. Experimental resultsobtained and presented for different working scenarios confirm the theoreticalresults, and they provide insight on how to improve the exploration of a searchspace that is too large to be searched exhaustively. 展开更多
关键词 Parallel instruction execution parallel algorithms genetic algorithms parallel genetic algorithms artificial intelligence techniques evolutionary strategies
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Genetic Algorithms to the Nesting Problem in the Leather Manufacturing Industry 认领 引用
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作者 张玉萍 蒋寿伟 尹忠慰 《Journal of Donghua University(English Edition)》 EI CAS 2005年第1期90-96,共7页
The nesting problem in the leather manufacturing is the problem of placing a set of irregularly shaped pieces (called stencils) on a set of irregularly shaped surfaces (called leathers sheets). This paper presents a n... The nesting problem in the leather manufacturing is the problem of placing a set of irregularly shaped pieces (called stencils) on a set of irregularly shaped surfaces (called leathers sheets). This paper presents a novel and promising processing approach. After the profile of leather sheets and stencils is obtained with digitizer, the discretization makes the processing independent of the specific geometrical information. The constraints of profile are regarded thoroughly. A heuristic bottom-left placement strategy is employed to sequentially locate stencils on sheets. The optimal placement sequence and rotation are deterimined by genetic algorithms (GA). A natural concise encoding method is developed to satisfy all the possible requirements of the leather nesting problem. The experimental results show that the proposed algorithm can not only be applied to the normal two-dimensional nesting problem, but also especially suitable for the placement of multiple two-dimensional irregular stencils on multiple two-dimensional irregular sheets. 展开更多
关键词 leather nesting genetic algorithms two-dimensional geometry irregular discretization.
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Reliability-Based Optimum Design of a Simple Offshore Platform Based on Genetic Algorithms 认领 引用
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作者 Zhang, LY Hu, YC Li, XJ 《China Ocean Engineering》 SCIE EI 1998年第1期43-52,共10页
In this paper, the problem of reliability-based optimal design of simple offshore platform is studied, and a nonlinear fatigue damage model based on damage mechanics and genetic algorithms are used in the fatigue reli... In this paper, the problem of reliability-based optimal design of simple offshore platform is studied, and a nonlinear fatigue damage model based on damage mechanics and genetic algorithms are used in the fatigue reliability optimum design of the structure under stochastic wave load. The fatigue damage model and the yield failure reliability analyzing model are used in the paper. The reliability of the models and the effectiveness of genetic algorithm are shown by the results of optimum design. 展开更多
关键词 damage mechanics genetic algorithms reliability-based optimum design fatigue reliability
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Dislocation parameters of Gonghe earthquake jointly inferred by using genetic algorithms and least squares method 认领 引用 被引量：1
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作者 王文萍 王庆良 《Acta Seismologica Sinica(English Edition)》 1999年第3期314-320,共7页
The Second Crustal Deformation Monitoring Center, China Seismological Bureau, has detected a marked uplift associated with the Gonghe Ms=7.0 earthquake on April 26, 1990, Qinghai Province. From the observed vertical d... The Second Crustal Deformation Monitoring Center, China Seismological Bureau, has detected a marked uplift associated with the Gonghe Ms=7.0 earthquake on April 26, 1990, Qinghai Province. From the observed vertical deformations and using a rectangular uniform slip model in a homogeneous elastic half space, we first employ genetic algorithms (GA) to infer the approximate global optimal solution, and further use least squares method to get more accurate global optimal solution by taking the approximate solution of GA as the initial parameters of least squares. The inversion results show that the causative fault of Gonghe Ms=7.0 earthquake is a right-lateral reverse fault with strike NW60°, dip SW and dip angle 37°, the coseismic fracture length, width and slip are 37 km, 6 km and 2.7 m respectively. Combination of GA and least squares algorithms is an effective joint inversion method, which could not only escape from local optimum of least squares, but also solve the slow convergence problem of GA after reaching adjacency of global optimal solution. 展开更多
关键词 genetic algorithms least squares method Gonghe earthquake dislocation model
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Optimization of perforation distribution for horizontal wells based on genetic algorithms 认领 引用 被引量：4
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作者 Wang Zhiming Wei Jianguang +2 位作者 Zhang Jian Gong Bin Yan Haiyun 《Petroleum Science》 SCIE CAS 2010年第2期232-238,共7页
Early water breakthrough and a rapid increase in water cut are always observed in high- permeability completion intervals when perforations are uniformly distributed in the wellbore in heterogeneous reservoirs. Optimi... Early water breakthrough and a rapid increase in water cut are always observed in high- permeability completion intervals when perforations are uniformly distributed in the wellbore in heterogeneous reservoirs. Optimization of perforating parameters in partitioned sections in horizontal intervals helps homogenize the inflow from the reservoir and thus is critically important for enhanced oil recovery. This paper derives a coupled reservoir-wellbore flow model based on inflow controlling theory. Genetic algorithms are applied to solving the model as they excel in obtaining the global optimum of discrete functions. The optimized perforating strategy applies a low perforation density in high- permeability intervals and a high perforation density in low-permeability intervals. As a result, the inflow profile is homogenized and idealized. 展开更多
关键词 Well completion perforation optimization genetic algorithms partition horizontal well
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