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2015 | 11 | 138-150
Article title

Use Genetic Algorithm in Optimization Function For Solving Queens Problem

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EN
Genetic algorithms are stochastic search techniques that guide a population of solutions towards an optimum using the principles of evolution and natural genetics. This paper shows the way that genetic algorithms can be used to solve 4-Queen problem. The NQP is a classical artificial intelligence problem. The N-Queens problem can be defined as follows: place N queens on an N x N chessboard, each queen on a square, so that no queen could capture any of the others, that is, a configuration in which there exists at most one queen on a given row, column or diagonal. Experimentally results shows that the genetic algorithm have the ability to find optimal solution or find solutions nearby optimal solutions. And The Genetic Algorithm is well suited to has been extensively applied to solve complex design optimization problems because it can handle both discrete and continuous variables, and nonlinear objective and constrain functions without requiring gradient information.
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11
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138-150
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References
  • [1] Ms. Dharmistha D. Vishwakarma” Genetic Algorithm based Weights Optimization of Artificial Neural Network”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 1(3) (2012).
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  • [8] Goldberg, David E. “Genetic Algorithm in Search, Optimization, and Machine Learning”, Addison Wesley Longmont, International Student Edition 1989.
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  • [10] Saif Hasan, Sagar Chordia, Rahul Varshneya,”Genetic algorithm”, February 6, 2012.
  • [11] Amer Draa, Souham Meshoul, Hichem Talbi, and Mohamed Batouche,,”A Quantum-Inspired Differential Evolution Algorithm for Solving the N-Queens Problem”, Computer Science Department, 2008.
  • [12] Marko Božikovic, Marin Golub, Leo Budin, “Solving n-Queen problem using global parallel genetic algorithm”, 2003.
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article
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YADDA identifier
bwmeta1.element.psjd-d4bf1c5e-9236-4968-88b3-aea49599b3b9
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