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Positioning of new mobile tower using Circle Packing Problem

EVOLUTIONARY INTELLIGENCE 2024年第5-6期17卷 3241-3268页

作者： Kumar, Yogesh Deep, Kusum Indian Inst Technol Roorkee Dept Math Roorkee 247667 Uttarakhand India

The Circle Packing Problem determines a circle of the largest area that can fit into the vacant space when n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{n}$$\end{document} arbitrary-sized non-overlapping given circles are placed inside a given container. One of its numerous applications is to determine the optimal positioning of mobile towers in a city. This constrained nonlinear optimization problem is solved using four variants of the real coded genetic Algorithm. These four variants are created by the combination of two well-known real-coded crossover operators: Arithmetic Crossover and Hybrid Crossover, and two well-known real-coded mutation operators: Uniform Mutation and Discrete Uniform Mutation. The performance of these algorithms is evaluated using the mean, standard deviation, best, worst of the objective function values and Friedman's mean ranking test is applied when 30 runs of each variants are carried out. On the basis of the computational analysis, the performance of the variant of RCGA having Arithmetic Crossover-Uniform Mutation (AX-UM) outperforms all other RCGAs considered in this study in terms of faster convergence and better accuracy of the solution. In a practical demonstration, this methodology is implemented to a case study in Roorkee City in Uttarakhand of Northen India. Currently, there are 14 existing mobile towers in Roorkee city. However, there are certain regions in which internet connectivity is unsatisfactory. Therefore, based on the recommendation of this study, AX-UM is recommended to install three new mobile towers.

关键词： real coded genetic algorithms Circle packing problem Crossover operators Mutation operators

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Evolutionary Neural Network Prediction for Cumulative Failure Modeling

Evolutionary Neural Network Prediction for Cumulative Failur...

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7th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA-09)

作者： Benaddy, M. Wakrim, M. Aljahdali, S. Dept. of Math. and Info. Equipe MMS Ibn Zohr University Morocco Taif University Saudi Arabia

ISBN: (纸本)9781424438075

An evolutionary neural network modeling approach for software cumulative failure prediction based on feed-forward neural network is proposed. A real coded genetic algorithm is used to optimize the mean square of the error produced by training a neural network established by Aljahdali S. [3]. In this paper we present a real coded genetic algorithm that uses the appropriate operators for this encoding type to train feed-forward neural network. We describe the genetic algorithm and we also experimentally compare our approach with the back propagation learning algorithm for the regression model order 4. Numerical results show that both the goodness-of-fit and the next-step-predictability of our proposed approach have greater accuracy in predicting software cumulative failure compared to other approaches.

关键词： genetic algorithms real coded genetic algorithms Feed-forward Neural Networks Software Reliability

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GAAP. genetic Algorithm with Auxiliary Populations Applied to Continuous Optimization Problems

GAAP. Genetic Algorithm with Auxiliary Populations Applied t...

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34th International Conference on Information Technology Interfaces (ITI)

作者： Corbalan, Leonardo Hasperue, Waldo Lanzarini, Laura Natl Univ La Plata Fac Comp Sci III LIDI Inst Res Comp Sci LIDI Buenos Aires DF Argentina

ISBN: (纸本)9789537138240;9781467316293

genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space.

关键词： real coded genetic algorithms continuous optimization early convergence exploration exploitation local search auxiliary populations

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Evolutionary Regression Prediction for Software Cumulative Failure Modeling: a comparative study

Evolutionary Regression Prediction for Software Cumulative F...

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International Conference on Multimedia Computing and Systems

作者： Benaddy, M. Wakrim, M. Aljandali, S. Dept. of Math. Info. Equipe MMS Ibn Zohr University Morocco Morocco Taif University Saudi Arabia Saudi Arabia

ISBN: (纸本)9781424437566

An evolutionary regression modeling approach for software cumulative failure prediction based on auto-regression order 4, 7 and 10 models are proposed. A real coded genetic algorithm is used to optimize the mean square of the error produced by training the auto-regression model. In this paper, we present a real coded genetic algorithm that uses the appropriate operators for this encoding type to train the auto-regression model. To evaluate the predictive capability of the developed model data sets, various projects were used. A comparison between auto-regression order 4 model trained using least square estimation [1] and real coded genetic algorithm training is provided, also a comparison between the auto-regression order 7 and 10 models trained using the genetic algorithm is presented. Experimental results show that the training of different auto-regression model by the real coded genetic algorithm has a good predictive capability.

关键词： genetic algorithms real coded genetic algorithms Auto Regression Model Software Reliability

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genetic algorithm based fuzzy weighted average for multi-criteria decision making problems

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OPSEARCH 2011年第2期48卷 96-108页

作者： Deep, Kusum Singh, Krishna Kansal, M. Indian Inst Technol Dept Math Roorkee 247667 Uttar Pradesh India Indian Inst Technol Dept Water Resources Dev & Management Roorkee 247667 Uttar Pradesh India Indian Inst Informat Technol Dept Informat Technol Allahabad 211012 Uttar Pradesh India

Ranking of alternatives on the basis of multi- criteria is an important issue in decision making. These criterion may be quantitative as well as qualitative in nature. In this paper, a method is developed using genetic algorithm for the ranking of alternatives on the basis of multi- criteria. Fuzzy numbers are used to evaluate the qualitative criteria. In this method, first, fuzzy weighted average of each alternative is formulated as a pair of non linear programs ( in the form of alpha-cut representation of fuzzy numbers), which represent the left and right bounds of alternative. After that, membership value of fuzzy weighted average of each alternative is constructed by enumerating different values of alpha. The pair of non linear optimization problems for different values of alpha are solved using genetic algorithm. Finally, ranking order of alternatives is calculated by Yager's ranking indices. A numerical example is solved successfully to demonstrate the proposed methodology.

关键词： Multi-criteria decision making Fuzzy number Fuzzy weighted average Nonlinear programming real coded genetic algorithms

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Designing optimum locations and properties of MTMD systems 5

Designing optimum locations and properties of MTMD systems

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5th Euro Asia Civil Engineering Forum (EACEF)

作者： Frans, Richard Arfiadi, Yoyong Atma Jaya Yogyakarta Univ Postgrad Program Civil Engn Yogyakarta 55281 Indonesia Atma Jaya Yogyakarta Univ Dept Civil Engn Jalan Babarsari 44 Yogyakarta 55281 Indonesia

Reducing vibration of buildings during earthquake is of the primary concern to most structural engineers. Several methods have been proposed including the use of damper systems. This paper considers the optimization procedures of multi tuned mass damper (MTMD) systems. A number of researches have considered designing MTMD systems to reduce structural response during earthquake. However, most of the research considered only the properties of the MTMD, while the locations of MTMD are decided beforehand. This paper considers the optimization both the properties and location of MTMD in structures. The hybrid coded genetic algorithms (HCGAs) are used to optimize the dampers. The HCGAs are the optimization method that utilize binary coded GAs (BCGAs) and real coded GAs (RCGAs). The RCGAs are used to optimize the properties of MTMD, while the BCGAs are utilized to optimize the location of the dampers. Numerical examples are then carried out to see the ability of the proposed method in optimizing the locations and the properties of the dampers. Numerical examples are carried out to a three, ten-, and forty-story buildings. For the three-and ten-story buildings, the location of the MTMD is obtained at the top of the buildings, whereas for forty-story building the location of the dampers is depending on the mass ratio of the dampers. For 1% mass ratio, the locations of the dampers, are at the 39th and 40th floors, respectively. For 2% mass ratio, the dampers locations are obtained at the 38th and 40th floor, respectively;while for 4% mass ratio, the dampers locations are at 37th and 40th floors, respectively. Numerical simulations show the effectiveness of MTMD systems in reducing response of structures due to earthquake. (C) 2015 The Authors. Published by Elsevier Ltd.

关键词： optimization binary genetic algorithms real coded genetic algorithms hybrid genetic algorithms multiple tuned mass dampers

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An Evolutionary Tomographic Reconstruction Procedure for Defect Identification Using Time-of-Flight of Ultrasound

An Evolutionary Tomographic Reconstruction Procedure for Def...

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International Conference on Evolution in Manufacturing (ICEM)

作者： Kodali, Shyam Prasad Rao, Boggarapu Nageswara Koneru Lakshmaiah Educ Fdn Dept Mech Engn Guntur 522502 Andhra Pradesh India

ISBN: (纸本)9789811652813;9789811652806

Structural integrity of engineering materials is influenced by external as well as internal defects. Tomographic reconstruction is useful for detection of internal defects in a nondestructive way. A novel tomographic reconstruction procedure is described and shown to have the potential to identify any defects present in a materials cross-section. The algorithm is designed in line with the principles of real coded genetic algorithms (RCGA). The proposed algorithm does not require the user to input exact characteristic property of material defects assumed to be present in the material cross-section being examined. The algorithm works its way with some finite range of the characteristic property as input. Results of several numerical studies demonstrate the effectiveness of proposed RCGA based reconstruction procedure.

关键词： Non-destructive testing Tomographic reconstruction real coded genetic algorithms Time-of-flight of ultrasound

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Reducing Response of Structures by Using Optimum Composite Tuned Mass Dampers

Reducing Response of Structures by Using Optimum Composite T...

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World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium (WMCAUS)

作者： Arfiadi, Yoyong Alma Jaya Yogyakarta Univ Jalan Babarsari 44 Yogyakarta 55281 Indonesia

In this paper, the optimization of composite tuned mass dampers in reducing the response of structures subject to earthquake are discussed. Composite tuned mass dampers are mass dampers that consist of two mass dampers connected in series. The mass of the auxiliary dampers is in general relatively smaller than the one of the first damper. However, in this paper the mass ratio of the auxiliary damper to total mass of dampers is varied from 0.1 up to 0.9;and the optimum stiffness and damping of the first and auxiliary dampers are obtained using real coded genetic algorithm (RCGA). From the result of optimization, it is found that the mass ratio of the auxiliary dampers does not significantly affect the response reduction of structures. It is also found that for a certain mass ratio, the resulting stiffness and damping are not unique for achieving the same performance. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： composite tuned mass dampers vibration control optimization real coded genetic algorithms

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Parent to Mean-Centric Self-Adaptation in SBX Operator for real-Parameter Optimization

Parent to Mean-Centric Self-Adaptation in SBX Operator for R...

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2nd Swarm, Evolutionary and Memetic Computing Conference (SEMCCO 2011)

作者： Jain, Himanshu Deb, Kalyanmoy Indian Inst Technol Dept Mech Engn Kanpur 208016 Uttar Pradesh India

ISBN: (纸本)9783642271717

Most real-parameter genetic algorithms (RGAs) use a blending of participating parent solutions to create offspring solutions in its recombination operator. The blending operation creates solutions either around one of the parent solutions (having a parent-centric approach) or around the centroid of the parent solutions (having a mean-centric approach). In this paper, we argue that a self-adaptive approach in which a parent or a mean-centric approach is adopted based on population statistics is a better procedure than either approach alone. We propose a self-adaptive simulated binary crossover (SA-SBX) approach for this purpose. On a test suite of six unimodal and multi-modal test problems, we demonstrate that a RGA with SA-SBX approach performs consistently better in locating the global optimum solution than RGA with original SBX operator and RGA with mean-centric SBX operator.

关键词： Self Adaptation real coded genetic algorithms Crossover

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Designing Optimum Locations and Properties of MTMD Systems

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Procedia Engineering 2015年 125卷 892-898页

作者： Richard Frans Yoyong Arfiadi Postgraduate Program of Civil Engineering Atma Jaya Yogyakarta University Yogyakarta 55281 Indonesia Department of Civil Engineering Atma Jaya Yogyakarta University Jalan Babarsari 44 Yogyakarta 55281 Indonesia

Reducing vibration of buildings during earthquake is of the primary concern to most structural engineers. Several methods have been proposed including the use of damper systems. This paper considers the optimization procedures of multi tuned mass damper (MTMD) systems. A number of researches have considered designing MTMD systems to reduce structural response during earthquake. However, most of the research considered only the properties of the MTMD, while the locations of MTMD are decided beforehand. This paper considers the optimization both the properties and location of MTMD in structures. The hybrid coded genetic algorithms (HCGAs) are used to optimize the dampers. The HCGAs are the optimization method that utilize binary coded GAs (BCGAs) and real coded GAs (RCGAs). The RCGAs are used to optimize the properties of MTMD, while the BCGAs are utilized to optimize the location of the dampers. Numerical examples are then carried out to see the ability of the proposed method in optimizing the locations and the properties of the dampers. Numerical examples are carried out to a three, ten-, and forty-story buildings. For the three- and ten-story buildings, the location of the MTMD is obtained at the top of the buildings, whereas for forty-story building the location of the dampers is depending on the mass ratio of the dampers. For 1% mass ratio, the locations of the dampers, are at the 39 th and 40 th floors, respectively. For 2% mass ratio, the dampers locations are obtained at the 38th and 40th floor, respectively; while for 4% mass ratio, the dampers locations are at 37 th and 40 th floors, respectively. Numerical simulations show the effectiveness of MTMD systems in reducing response of structures due to earthquake.

关键词： optimization binary genetic algorithms real coded genetic algorithms hybrid genetic algorithms multiple tuned mass dampers

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