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检索条件"任意字段=10th Conference on Foundations of Genetic Algorithms"

共 1409 条记录，以下是51-60 订阅

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Application of Evolutionary and Hybrid algorithms to Optimize Investments Strategies in Large Power Plants

Application of Evolutionary and Hybrid Algorithms to Optimiz...

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10th International conference on Probabilistic Methods Applied to Power Systems

作者： Sakowicz, Bartosz Anders, George J. Kaminski, Marek Napieralski, Andrzej Tech Univ Lodz Dept Microelect & Comp Sci PL-90924 Lodz Poland

ISBN: (纸本)9781934325216

this article is an extension of the work presented earlier, which compared and analyzed the economics of alternative maintenance plans. the proposed model combines genetic algorithms with Monte Carlo simulation to arrive at the most economic investment timing. the approach described earlier was characterized by a very long computing time making it difficult to use. this paper addresses several issues related to the computational efficiency and introduces several innovative solutions that not only improve the accuracy of the analysis but also provide new opportunities in selecting optimal investment scenarios. the methodology based on stochastic-deterministic optimization algorithms and activation genes is described and illustrated by a numerical example involving analysis of the optimal number of new investments and their most economic timing for a refurbishment of a large steam generating unit.

关键词： life cycle management evolutionary algorithms genetic algorithms stochastic optimization

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the research of the hierarchical structure characteristic mechanical product conceptual design based on genetic algorithms

The research of the hierarchical structure characteristic me...

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10th World Multi-conference on Systemics, Cybernetics and Informatics/12th International conference on Information Systems Analysis and Synthesis

作者： Bo, Hao Wang Lixin Weng Zhifeng Jiang Mingyang Shenyang Ligong Univ Sch Mech Engn Shenyang 110168 Peoples R China

ISBN: (纸本)9789806560727

Conceptual design is a vital aspect of design process. the quality of product is directly influenced by Conceptual design. the science and technology rapid development, the product function request increases day by day, the complexity increases, the average life reduces, the renewal speed speeds up. However, conceptual design, in particular mechanical product conceptual design method, then appears lacks the ability cannot follow time the need to develop. this article in analyzes the hierarchical mechanical product structure characteristic in the foundation, in view of had the hierarchical structure characteristic mechanical product the holistic conceptual design to propose the hierarchical gene code technology,, and in the knowledge evolution algorithm - genetic algorithms foundation, the genetic algorithms and the mechanical pi duct holistic conceptual design will unify, proposed face the hierarchical structure mechanical product holistic conceptual design genetic algorithms CAD design model. According to this design model, applied the Visual C++6.0 and the SQL-Server2000 database software and has completed facing the hierarchical structure mechanical product holistic conceptual design genetic algorithms in the numerical control lathe holistic conceptual design practical application system development. Has established the numerical control lathe holistic conceptual design system, this system can complete the numerical control lathe holistic conceptual design, obtained the mod result through the actual use.

关键词： holistic conceptual design genetic algorithms numerical control lathe intelligent creative design

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Analysis of Global Exploration of Island Model genetic Algorithm

Analysis of Global Exploration of Island Model Genetic Algor...

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10th International conference on the Experience of Designing and Application of CAD Systems in Microelectronics

作者： Artyushenko, Bogdan Zaporizhzhya Natl Tech Univ Dept Design & Prod Technol Radio Equipment UA-69000 Zaporizhzhya Ukraine

Island model genetic algorithms are fast spreading optimization method because of their parallel nature. We focus on the global exploration capabilities of mutation-based algorithms. Using a simple bimodal test functi... 详细信息

ISBN: (纸本)9789531841306

关键词： genetic algorithm island model diversity mechanism exploration

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Automated Unit Test Generation for Evolving Software 2015

Automated Unit Test Generation for Evolving Software

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10th Joint Meeting of the European Software Engineering conference (ESEC) / ACM SIGSOFT Symposium on the foundations of Software Engineering (FSE)

作者： Shamshiri, Sina Univ Sheffield Dept Comp Sci 211 Portobello Sheffield S1 4DP S Yorkshire England

ISBN: (纸本)9781450336758

As developers make changes to software programs, they want to ensure that the originally intended functionality of the software has not been affected. As a result, developers write tests and execute them after making changes. However, high quality tests are needed that can reveal unintended bugs, and not all developers have access to such tests. Moreover, since tests are written without the knowledge of future changes, sometimes new tests are needed to exercise such changes. While this problem has been well studied in the literature, the current approaches for automatically generating such tests either only attempt to reach the change and do not aim to propagate the infected state to the output, or may suffer from scalability issues, especially when a large sequence of calls is required for propagation. We propose a search-based approach that aims to automatically generate tests which can reveal functionality changes, given two versions of a program (e.g., pre-change and post-change). Developers can then use these tests to identify unintended functionality changes (i.e., bugs). Initial evaluation results show that our approach can be effective on detecting such changes, but there remain challenges in scaling up test generation and making the tests useful to developers, both of which we aim to overcome.

关键词： Automated Unit Test Generation genetic algorithms Search-Based Testing Regression Testing

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Solving Sudoku Puzzles with Node Based Coincidence Algorithm

Solving Sudoku Puzzles with Node Based Coincidence Algorithm

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10th International Joint conference on Computer Science and Software Engineering (JCSSE)

作者： Waiyapara, Kiatsopon Wattanapornprom, Warin Chongstitvatana, Prabhas Chulalongkorn Univ Fac Engn Dept Compute Engn Bangkok Thailand Chulalongkorn Univ Fac Engn Dept Comp Engn Bangkok Thailand

ISBN: (纸本)9781479908066;9781479908059

In Evolutionary computation, Sudoku puzzles are categorized as hard combinatorial problems. It is almost impossible to solve these puzzles using only native operations of genetic algorithms. this article presents an application of Coincidence algorithm, which is an Estimation of distribution algorithms in the class of evolutionary computation that can outperform traditional algorithms on several combinatorial problems. It makes use of both positive and negative knowledge for solving problems. the proposed method is compared with the current best known method. It significantly outperforms problem-specific GA to solve easy, medium, and hard level of Sudoku puzzles.

关键词： Coincidence Algorithm Sudoku Puzzle Multimodal Optimization Estimation of Distribution algorithms genetic Algorithm

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Component-based Visual Evolutionary Computation 10

Component-based Visual Evolutionary Computation

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10th Computing Colombian conference (10CCC)

作者： Garzon, Leidy Rodriguez, Nestor Orjuela, Henry Rojas-Galeano, Sergio DreamGis SAS Bogota Colombia CHECK24 Vergleichsportal GmbH Munich Area Germany Univ Distrital Sch Engn Bogota Colombia

ISBN: (纸本)9781467394642

Component-based computation advocates for building systems by assembling prefabricated self-contained software modules within a formally specified composition model. Furthermore, visual components allow users to perform such assemblage in a friendly graphical board were components are connected visually with virtually no coding needed. Recently, an Evolutionary Computation (EC) suite of components called Goldenberry complying with such premises has been released. In this paper we demonstrate its feasibility in several EC tasks: optimisation of continuous-valued and discrete-valued costs functions using genetic algorithms and Estimation of Distribution algorithms as well as feature selection algorithms and relevance estimation in data mining tasks. We discuss the advantages and weaknesses of the approach and the toolbox, its differences with other existing software tools and proposing avenues of future development. Goldenberry is open-source under the New BSD License and it is available at: http://***

关键词： data mining distributed algorithms feature selection formal specification genetic algorithms object-oriented programming public domain software BSD license EC suite Goldenberry component-based visual evolutionary computation continuous-valued cost function optimisation data mining tasks discrete-valued cost function optimisation distribution algorithm estimation feature selection algorithms formally specified composition model friendly-graphical board open-source software prefabricated self-contained software module assembling relevance estimation software tools visual components Benchmark testing Cost function genetic algorithms Sociology Software Visualization

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genetic algorithm based path planning and optimization for autonomous mobile robots with morphological preprocessing

Genetic algorithm based path planning and optimization for a...

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10th IEEE International Multitopic conference

作者： Afsar, Fayyaz A. Arif, M. Hussain, M. Pakistan Inst Engn & Appl Sci Dept Elect Engn PO Nilore Islamabad Pakistan Pakistan Inst Engn & Appl Sci Dept Comp & Informat Sci Islamabad Pakistan

ISBN: (纸本)9781424407941

this paper presents an algorithm for optimal path planning for mobile robots using genetic algorithms coupled with morphological image preprocessing of the terrain. Path Planning in a given environment, being a NP-Hard problem, is computationally demanding especially if exact or deterministic techniques are employed. this paves the way for the use of evolutionary computing techniques, such as genetic algorithms (GAs), for the solution of this problem. However as GAs tend to find optimal paths without considering the location and distribution of obstacles in the given map, therefore a large amount of time may be spent before even a feasible path is found. the technique conferred in this paper overcomes this shortcoming by using specialized morphological preprocessing techniques applied on the landscape representative image. the results obtained on a variety of structured, unstructured and clustered terrains indicate the efficacy of the algorithm presented and the potential for the use of this algorithm in real-time operation of mobile robots.

关键词： path planning for robots optimization genetic algorithms morphological processing

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genetic algorithms and grid computing for artificial embryogeny 08

Genetic algorithms and grid computing for artificial embryog...

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10th Annual genetic and Evolutionary Computation conference, GECCO 2008

作者： Cussat-Blanc, Sylvain Luga, Hervé Duthen, Yves Viale, Fabien Caromel, Denis IRIT CNRS Université de Toulouse France INRIA Sophia Antipolis France

ISBN: (纸本)9781605581309

genetic algorithms are very demanding in terms of computing time and, when the population size is large, they need days to complete or even fail due to memory restrictions. It is particularly the case for artificial life where each evaluation can take more than one minute to develop an artificial creature, plant or organism. Indeed, creatures are developed in physical and chemical simulators that require important computation resources. In order to create more and more realistic creatures, we propose a grid parallelized version of genetic algorithms. Two possibilities exist to increase them: supercomputers or computational grids. Because of their scalability, we choose computational grid in their works.

关键词： genetic algorithms

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Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata 08

Self-adaptive mutation rates in genetic algorithm for invers...

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10th Annual genetic and Evolutionary Computation conference, GECCO 2008

作者： Breukelaar, Ron Bäck, thomas Leiden Institute of Advanced Computer Science Universiteit Leiden P.O. Box 9512 2300 RA Leiden Netherlands Blueridge Analytics Inc. 101 W. Worthington Ave. Charlotte NC 28203 United States Nutech Solutions GmbH Martin-Schmeisser-Weg 44227 Dortmund Germany

ISBN: (纸本)9781605581309

Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for genetic algorithms. this poster describes how a self-adaptive mutation rate was used in a genetic algorithms to inverse design behavioral rules for a Cellular Automata. the unique characteristics of this search space gave rise to some interesting convergence behavior that might have implications for using self-adaptive mutation rates in other genetic Algorithm applications and might clarify why self-adaptation in genetic algorithms is less successful than in Evolutionary Strategies.

关键词： genetic algorithms

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Evolving combat algorithms to control space ships in a 2D space simulation game with co-evolution using genetic programming and decision trees 08

Evolving combat algorithms to control space ships in a 2D sp...

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10th Annual genetic and Evolutionary Computation conference, GECCO 2008

作者： Francisco, Tiago Dos Reis, Gustavo Miguel Jorge School of Technology and Management Polytechnic Institute of Leiria Portugal

ISBN: (纸本)9781605581309

Developing artificial behaviours to control artificial creatures or vehicles is a task that can be employed by means of Evolutionary algorithms. A game's artificial intelligence is usually developed by seasoned game developers, which need critical knowledge of the games mechanics and rules. this paper presents an alternative, using evolutionary computation to evolve combat algorithms that will allow spaceships to fight effectively in a 2D space simulation game. these combat algorithms will take into account the spaceships characteristics, using them to gain the advantage needed to fight effectively Copyright 2008 ACM.

关键词： genetic programming

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