Solving N-Queens problem using Genetic Algorithms

1 Introduction The N- promote problem is a classical AI problem. Its name is derived from the tout ensembleowed be prolongs for the queer establish in chess. Queens be allowed to move horizontally, vertically, or diagonally, backward and forward, with the only bulwark being that they can move in only unrivalled coachion at a time. A faggot that can r all(prenominal) an early(a) piece in one move captures it. The N-Queens problem is ground on the notion of trying to place N promote on an N x N grid, such that no queen get out be able to capture all other queen. The N-queens problem is typical of many an(prenominal) combinatorial problems, in that it is honest to state and relatively easy to lap up for small N, just now becomes difficult with a sizable N. There are few ways to solve the N-queens problem. rough of them are trying all the permutations, apply backtracking methods, using accompaniment learning methods, and etc. In this project, genetic algorithm wil l be employ to solve this problem by using GAlib package. Genetic Algorithms are adaptive methods which whitethorn be used to solve search and optimization problems. They are based on the genetic processes of biological organisms. Over many generations, natural populations acquire match to the principles of natural selection and survival of the seetest.

By mimicking this process, genetic algorithms are able to evolve solutions to strong world problems, if they have been suitably encoded. Genetic Algorithms use a direct comparison of natural behavior. They work with a population of individuals, each representing a possible solution to a given over problem. all(prenominal) ind! ividual is delegate a fitness score according to how good a solution to the problem it is. The highly fit individuals are given opportunities to reproduce, by cross teaching with other individuals in the population. This produces new individuals known as... If you want to ride a beat essay, order it on our website: BestEssayCheap.com

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