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Evolutionary algorithms for the Component Selection Problem

Evolutionary Algorithms for the Component Selection Problem

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international workshop on Database and Expert Systems applications

作者： Andreea Vescan Crina Grosan Horia F. Pop Department of Computer Science Babeş-Bolyai University Cluj-Napoca Romania

Component selection is a crucial problem in component based software engineering. Component based software engineering (CBSE) is concerned with the assembly of pre-existing software components that leads to a software system that responds to client-specific requirements. We are approaching the component selection involving dependencies between components (requirements). We formulate the problem as multiobjective. The approach used is an evolutionary computation technique. Various representations were used with various applied methods to deal with the multiobjectives.

关键词： Software Strontium optimization Computational modeling Evolutionary computation Conferences Software engineering

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optimization of time domain models applied to structural health monitoring 4

Optimization of time domain models applied to structural hea...

引用

4th international workshop on Structural Health Monitoring: From Diagnostics and Prognostics to Structural Health Management, IWSHM 2003

作者： Allen, D.W. Inmann, D.J. Farrar, C.R. Center for Intelligent Material Systems and Structures Virginia Polytechnic Institute 310 Durham Hall MC 0261 BlacksburgVA24061 United States Engineering Sciences and Applications - Weapons Response Los Alamos National Laboratory MS T006 PO Box 1663 Los AlamosNM87545 United States

ISBN: (纸本)1932078207

Many new approaches for extracting damage sensitive features for structural health monitoring include the use of time series modeling. Time series models are being explored to avoid computationally expensive transforms of data into the frequency domain and the ability to remove environmental and operational variability from the data through normalization. The process of fitting time series models requires that an appropriate model and order of the model be chosen. The order is crucial to the accuracy and computational overhead of the model. Models with too low of an order may fail to capture the underlying mechanism of the system, while models with to high of an order will begin fitting error in the system becoming less robust. Computational efficiency is also becoming critical as structural health monitoring technology moves closer to implementing algorithms on distributed integrated systems consisting of a sensor, transmitter and a processor with limited resources. Typically, order estimation is preformed manually by observing several diagnostics;in this paper however, criteria that may be extended to an automated procedure for selecting the optimal model order are explored. These criteria are applied to optimize the order of a simple ARMA model for an eight degree-of-freedom system. Results from the criteria are compared to each other and to a manual estimation. Copyright © 2003 by DEStech Publications, Inc. All right reserved.

关键词： Structural health monitoring

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First Studies to Apply the Theory of Mind Theory to Green and Smart Mobility by Using Gaussian Area Clustering

First Studies to Apply the Theory of Mind Theory to Green an...

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2021 international Conference of Yearly Reports on Informatics, Mathematics and Engineering, ICYRIME 2021

作者： Brandizzi, Nicolo Russo, Samuele Brociek, Rafal Wajda, Agata Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00135 Italy Department of Psychology Sapienza University of Rome via dei Marsi 78 Roma00185 Italy Department of Mathematics Applications and Methods for Artificial Intelligence Faculty of Applied Mathematics Silesian University of Technology Gliwice44-100 Poland

This paper investigates emerging pattern in users green and smart mobility. Our focus is finding an optimal clusterization of vehicles based on user demand in the metropolitan city of Barcelona and analyze the users' behavior with a theory of mind framework. The notions of clusters, algorithms definitions and optimization procedure are introduced in this study. The following assumption will be considered: the task is a dynamic multi-agent problem settled in a city on a group of scooters. Given the conditions and the data set, the algorithm consists of two phases. First we estimate the vehicles density during the day, hour and location, and we analyze the users' behavior and draw conclusion on their habits. Then we propose a unsupervised clustering technique based on Gaussian area, that takes into consideration point of interests and dis-interest, shaping the area accordingly. Our focus is on simplicity and reproducibility, for this reason our formulation and solution can be considered a general approach that can be adapted based on specific needs. © 2021 Copyright for this paper by its authors

关键词： Multi agent systems

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2nd international workshop on Grid and Cooperative Computing, GCC 2003

2nd International Workshop on Grid and Cooperative Computing...

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2nd international workshop on Grid and Cooperative Computing, GCC 2003

ISBN: (纸本)3540219935

The proceedings contain 169 papers. The special focus in this conference is on Advanced Resource Management, Scheduling, and Monitoring. The topics include: Synthetic implementations of performance data collection in massively parallel systems;a GMA-based monitoring and management infrastructure for grid;a parallel branch-and-bound algorithm for computing optimal task graph schedules;selection and advanced reservation of backup resources for high availability service in computational grid;an online scheduling algorithm for grid computing systems;a dynamic job scheduling algorithm for computational grid;an integrated management and scheduling scheme for computational grid;multisite task scheduling on distributed computing grid;adaptive job scheduling for a service grid using a genetic algorithm;resource scheduling algorithms for grid computing and its modeling and analysis using petri net;architecture of grid resource allocation management based on QoS;an improved ganglia-like clusters monitoring system;effective openMP extensions for irregular applications on cluster environments;a scheduling approach with respect to overlap of computing and data transferring in grid computing;a deadline and budget constrained cost-time optimization algorithm for scheduling dependent tasks in grid computing;a load balancing algorithm for web based server grids;flexible intermediate library for MPI-2 support on an score cluster system;resource management and scheduling in manufacturing grid;a new task scheduling algorithm in distributed computing environments;grid monitoring system based on mobile agent;grid-based resource management of naval weapon systems and a static task scheduling algorithm in grid computing.

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Model-driven multi-quality auto-Tuning of robotic applications 15

Model-driven multi-quality auto-Tuning of robotic applicatio...

引用

Joint MORSE/VAO workshop on Model-Driven Robot Software Engineering and View-Based Software-Engineering, MORSE/VAO 2015

作者： Piechnick, Christian Götz, Sebastian Schöne, Rene Abmann, Uwe Technische Universität Dresden Nöthnitzer Str. 46 Dresden01187 Germany

ISBN: (纸本)9781450336147

For the Simultaneous Localization and Mapping (SLAM) problem, many implementations exist, which meet different requirements w.r.t. non-functional properties (e.g., performance). If those requirements change during runtime, the application should change the SLAM implementation. Implementing the selection of the optimal SLAM-algorithms for robots by hand is time consuming and leads to bad code maintainability by mixing application and adaptation logic. Moreover, the realization of the optimization in code requires the developer to re-implement parts of general purpose optimizers, which impairs reusability. An external adaptation logic selecting the optimal SLAM algorithm addresses the maintainability and programmability issues. A model-driven approach for both, application and selection problem, highly increases reusability. To reach these goals, we propose to use Multi-Quality Auto-Tuning (MQuAT), a model-driven approach to build and operate self-optimizing systems following the Models@*** paradigm. We evaluate our approach by a case study, where robots have to choose between several variants of a distributed SLAM algorithm. © 2015 ACM.

关键词： Reusability

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Multi-criteria Manipulator Trajectory optimization Based on Evolutionary algorithms 5th

Multi-criteria Manipulator Trajectory Optimization Based on ...

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5th international workshop on Soft Computing Models in Industrial applications , SOCO 2010

作者： Pires, E. J. Solteiro Oliveira, P. B. de Moura Machado, J. A. Tenreiro Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas Escola de Ciências e Tecnologia da Universidade de Trás-os-Montes e Alto Douro Quinta de Prados Vila Real5000–801 Portugal Instituto Superior de Engenharia do Porto Instituto Politécnico do Porto Portugal

ISBN: (纸本)9783642131608

This paper proposes a method, based on a genetic algorithm, to generate smoth manipulator trajectories in a multi-objective perspective. The method uses terms proportional to the integral of the squared displacements in order to eliminate the jerk movement. In this work, the algorithm, based on NSGA-II and maximin sorting schemes, considers manipulators of two, three and four rotational axis (2R, 3R, 4R). The efficiency of the algorithm is evaluated, namely the extension of the front and the dispersion along the front. The effectiveness and capacity of the proposed approach are shown through simulations tests. © Springer-Verlag Berlin Heidelberg 2010.

关键词： Manipulators

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A Bottom-Up Method for Facial Feature Extraction Using Active Shape Models

A Bottom-Up Method for Facial Feature Extraction Using Activ...

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international workshop on Intelligent Systems and applications, ISA

作者： Min Jiang Qin Xu Tao Shang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China College of Computer Science and Technology School of Information Science and Technology Wuhan China

Facial feature extraction attracts much research interest due to its importance value in applications including human-computer interaction and visual surveillance. Model-based algorithms such as active shape models and active appearance models are efficient for facial feature extraction in color images. However, the complexity of the images and the local nature of active shape models optimization presents a challenge to the localization problem . We propose a new bottom-up method in model fitting stage of ASM, which decompose the whole face model search into several sub-feature *** enables the models to be combined with other feature location methods as to get good initialization and lead to more accurate estimates. We demonstrate the experiment results of successfully applying this schema on facial feature extraction.

关键词： Facial features Active shape model Active appearance model Data mining Eyebrows optimization methods Educational institutions Computer science Information science Application software

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Dependability of on-line optimization techniques in real-time applications

Dependability of on-line optimization techniques in real-tim...

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international workshop on Object Orientation in Operating Systems

作者： Hamidzadeh Shekhar Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Department of Computer Science University of Minnesota Minneapolis MN USA

Real-time problem solvers require dependable, real-time search algorithms to meet task deadlines and to predict deadline violations. Presently it is difficult for existing real-time search algorithms to search and execute the solution by the deadline and to make deadline violation prediction. We introduce a real-time search algorithm called Self-Adjusting Real-Time Search (SARTS). Given a timing constraint, SARTS adjusts itself based on the remaining time to deadline and allocates the planning time. As the timing constraints are relaxed, it will continue to improve its solutions progressively. The algorithm is able to predict deadline violations. Theoretical analyses and experimental results reveal that, compared to the existing techniques, SARTS demonstrates a higher degree of predictability and a higher deadline compliance ability.

关键词： optimization methods

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A new hybrid heuristic technique for solving job-shop scheduling problem

A new hybrid heuristic technique for solving job-shop schedu...

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Cheng-Fa Tsai Feng-Cheng Lin Department of Management Information Systems National Pingtung University of Science and Technology Ping Tung Taiwan

ISBN: (纸本)0780381386

We propose a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA algorithm) outperforms several currently used approaches. This investigation also considers a real-life job-shop scheduling system design, which optimizes the performance of the job-shop scheduling system subject to a required service level. Simulation results demonstrate that the proposed method is very efficient and potentially useful in solving job-shop scheduling problems

关键词： Genetic algorithms Design optimization Simulated annealing Biological cells Management information systems Uniform resource locators Heuristic algorithms Neural networks Crystallization Physics

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A genetic algorithm for the reliability optimization of a distributed system

A genetic algorithm for the reliability optimization of a di...

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international workshop on Database and Expert Systems applications

作者： Ruey-Shun Chen Chin Ching Chiu Y.S. Yeh Institute of Information Management National Chiao Tung University Hsinchu Taiwan Institute of Computer Science and Information Engineering National Chiao Tung University Hsinchu Taiwan

The widespread use of distributed systems (DS) over the centralized systems can be attributed partially to its potential to enhance system reliability. In the reliability analysis of a DS, S-node Reliability (SNR) is defined as the probabilities that all nodes in S (a subset of all processing elements) are connected. SNR optimization for the distributed systems Exact Method (EM) has received only limited attention owing to the fact that computing reliability of DS is in general an NP-hard problem. Genetic algorithms (GA) are search techniques for global optimization in a complex search space. GA can be applied to search a large, multimodel, complex problem spaces. Thus, there is a good potential to obtain optimal and near optimal results using GA for network reliability problem. In this work, we attempt to reduce computational time and complexity by presenting a method based on a Genetic Algorithm S-Node set Reliability Methodology (GASNR) to optimize a specified object function under a given capacity constraint. The versatility of genetic algorithms is illustrated by applying them to solve the S-node set reliability problem. Using GASNR to find the best S-node sets. Because the final number of best S-node sets is only one, we just take less time to compute the reliability using SYREL. In addition, the proposed algorithm is compared with the existing one for various topologies. Those results demonstrate that for a large DS, the proposed algorithm is more efficient in execution time.

关键词： Genetic algorithms Telecommunication network reliability optimization methods Network topology Computer networks Computer network reliability Distributed computing Costs Resource management Information management

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