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15 results for “crossover and mutation”

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Research ArticleOpen accessIn the keywordsAn Improved Clustering Based Genetic Algorithm for Solving Complex NP ProblemsR. Sivaraj, T. RavichandranProblem statement: The selection process is a major factor in genetic algorithm which determines the optimality of solution for a complex problem. The selection pressure is the critical step which finds out the best individuals in the entire population for further genetic operators. The proposed algorithm tries to find out the best individuals with reduced selection pressure than standard genetic … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,928 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSolving the Traveling Salesman Problem Using New Operators in Genetic AlgorithmsNaef Taher Al Rahedi, Jalal AtoumProblem statement: Genetic Algorithms (GAs) have been used as search algorithms to find near-optimal solutions for many NP problems. GAs require effective chromosome representations as well as carefully designed crossover and mutation operators to achieve an efficient search. The Traveling Salesman Problem (TSP), as an NP search problem, involves finding the shortest Hamiltonian Path or Cycle in a graph of … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 7,584 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPerformance Analysis of Multi Clustered Parallel Genetic Algorithm with Gray ValueP. Vishnu Raja, V. Murali BhaskaranProblem statement: Encoding is one of the major factors in genetic algorithms, for a complex problem the optimality for the problem is determined. The encoding mechanism is the initial step which forms the chromosome to form the best fit individuals in the entire population. The proposed method tries to encode the initial population by the binary encoding and by gray … …American Journal of Applied Sciences, Vol. 9, Issue 8 · 28 Jun 2012 · 7,163 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFeature Selection in Data-Mining for Genetics Using Genetic AlgorithmV. N. Rajavarman, S. P. RajagopalanWe discovered genetic features and environmental factors which were involved in multifactorial diseases. To exploit the massive data obtained from the experiments conducted at the General Hospital, Chennai, data mining tools were required and we proposed a 2-Phase approach using a specific genetic algorithm. This heuristic approach had been chosen as the number of features to consider was large (upto … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,627 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Nested Digital Watermarking Scheme Using GARN with DWTEdward Yellakour Baagyere, Peter Awonnatemi Agbedemnab, Mohammed Akolgo, Strato Angsoteng BayitaaCopyright infringement is undoubtedly one of the major challenges in the film and TV industries over the years but has become even more pervasive lately as a result of technological advancement. This has made it possible to decode hitherto, hard-encoded, or encrypted multimedia content resulting in a lot of losses to companies in such industries. Digital watermarking, which is, a … …Journal of Computer Science, Vol. 20, Issue 10 · 30 Jul 2024 · 4,793 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Ant Colony Optimization and Genetic Algorithm for Rule InductionHayder Naser Khraibet AL-Behadili, Ku Ruhana Ku-Mahamud, Rafid SagbanIn this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. The Ant-Miner classifier is efficient, useful and commonly used for solving rule-based classification problems in data mining. Ant-Miner, which is an ACO variant, suffers from local optimization problem which affects its performance. In our … …Journal of Computer Science, Vol. 16, Issue 7 · 24 Jul 2020 · 7,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter Settings for New Generational Genetic Algorithms for Solving Global Optimization ProblemsSiew Mooi Lim, Md. Nasir Sulaiman, Norwati Mustapha, Abu Bakar Md. SultanThis study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent. …Journal of Computer Science, Vol. 11, Issue 11 · 7 Jan 2016 · 6,404 accessesView PDFCite
Research ArticleOpen accessIn the abstractCONSTRAINT INFORMATIVE RULES FOR GENETIC ALGORITHM-BASED WEB PAGE RECOMMENDATION SYSTEMS. Prince Mary, E. BaburajTo predict the users navigation using web usage mining is the primary motto of the web page recommendation. Currently, researchers are trying to develop a web page recommendation using pattern mining technique. Here, we propose a technique for web page recommendation using genetic algorithm. It consists of three phases as data preparation, mining of informative rules and recommendation. The data … …Journal of Computer Science, Vol. 9, Issue 11 · 5 Oct 2013 · 6,670 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Tool for Generation and Minimization of Test Suite by Mutant Gene AlgorithmSelvakumar Subramanian, Ramaraj NatarajanProblem statement: This study proposes a new idea for generation of minimized test suite in the test case generation using the mutant gene algorithm, which not only identifies the best test cases but also reduces the number of test cases generated, selects test cases optimally there improving the performance in testing of software. Test cases are generated by using branch … …Journal of Computer Science, Vol. 7, Issue 10 · 9 Aug 2011 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Genetic Algorithm Based Multi Objective Service Restoration in Distribution SystemsSathish Kumar Kannaiah, Jayabarathi Thangavel, D. P. KothariProblem statement: A Genetic Algorithm (GA) used here to find exact or approximate solutions to optimization and search problems. Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection and crossover. Approach: GA is a method for search and optimization based on the process of natural selection and evolution. … …Journal of Computer Science, Vol. 7, Issue 3 · 9 Mar 2011 · 7,029 accessesView PDFCite