Paper, 4 p, IAENG International Journal of Applied Mathematics. The paper attempts to solve the generalized Assignment problem through genetic algorithm and simulated annealing. The generalized assignment problem is basically the N men- N jobs problem where a single job can be assigned to only one person in such a way that the overall cost of assignment is minimized. While...
Paper, Int. J. Elect. Enging. Educ., Vol. 36, pp. 139– 153. Manchester U.P., 1999. Printed in Great Britain In this paper, an attractive approach for teaching genetic algorithm (GA) is presented. This approach is based primarily on using MatLAB in implementing the genetic operators: crossover, mutation and selection. A detailed illustrative example is presented to demonstrate...
Paper, 13 p, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 1, No 1, January 2013 The overall aim of the software industry is to ensure delivery of high quality software to the end user. To ensure high quality software, it is required to test software. Testing ensures that software meets user specifications and requirements. However, the field of...
Paper , Modern Applied Science, Vol. 5, No. 1, 6 p, February 2011 The genetic algorithm is briefly introduced and its complete programming is provided in detail by MatLAB 7.0. In addition, the application in optimization of functions and solution of equation is shown through three examples and the method of avoiding local optimization by increasing the value of pm is also...
Paper, Indonesian Institute of Sciences (LIPI), Indonesia, 10 p. This paper explains genetic algorithm for novice in this field. Basic philosophy of genetic algorithm and its flowchart are described. Step by step numerical computation of genetic algorithm for solving simple mathematical equality problem will be briefly explained.
Paper, Intelligent Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms, Ch.1, pp.1–33,USA, September, 1997 Fuzzy theory and systems Aspects of fuzzy systems Mathematical model-based control and rule-based control Design of antecedent parts Design of consequent parts Fuzzy reasoning and aggregation Analogy from biological neural networks Several types of artificial...
Paper, 35 p, Department of Computer Science – University College London. Interest in Genetic algorithms is expanding rapidly. This paper reviews software environments for programming Genetic Algorithms (GAs). As background, we initially preview genetic algorithms' models and their programming. Next we classify GA software environments into three main categories:...
Paper, Institute of Control and Industrial Informatics, 6 p Evolutionary algorithms (EA) represent a powerful optimization approach, which mimics the process of natural evolution. These algorithms are successful in solving complex problems. But in practical applications the computation time also under the use of such algorithms can be very long. In this paper we present a grid...
Paper, 37 p, Journal of Statistical Software, April 2013, Volume 53, Issue 4. Genetic algorithms (GAs) are stochastic search algorithms inspired by the basic principles of biological evolution and natural selection. GAs simulate the evolution of living organisms, where the ttest individuals dominate over the weaker ones, by mimicking the biological mechanisms of evolution, such...
Paper, 9 p. The paper deals with the cluster analysis and genetic algorithms and describes their basis. The application of genetic algorithms is focused on a cluster analysis as an optimization task. The case studies present the way of solution of two and three dimensional cluster analysis in MatLAB program with use of the Genetic Algorithm and Direct Search Toolbox. The way of...
Paper, SIGAda, November 14–18, 2004, Atlanta, Georgia, USA. Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is evolved from a set of potential solutions, known as a population. GAs accomplish this evolutionary process through the use of basic operators, crossover and mutation. Both the...
Paper, 6 p, World Academy of Science, Engineering and Technology. This paper presents a method for the optimal allocation of Distributed generation in distribution systems. In this paper, our aim would be optimal distributed generation allocation for voltage profile improvement and loss reduction in distribution network. Genetic Algorithm (GA) was used as the solving tool,...
Paper, 7 p, International Journal of Latest Trends in Engineering and Technology, Vol. 3 Issue 3 January 2014. In this paper we have gone through a very brief idea on Genetic Algorithm, which is a very new approach for problems related to Optimization. There are many techniques used to optimize a function but in case of optimizing Multimodal Functions most of these techniques...
Paper, 12 p, International journal of optimization in civil engineering, 2012. Equipment selection is a key factor in modern construction industry. As it is a complex factor, current models offered by literatures fail to provide adequate solutions for major issues like systematic evaluation of soft factors and weighting of soft benefits in comparison with costs. This paper aims...
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