文章基本信息

标题：Solving NP hard Problems using Genetic Algorithm
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作者：Gaurang Panchal ; Devyani Panchal
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：2
页码：1824-1827
出版社：TechScience Publications
摘要：The use of genetic algorithms was originally motivated by the astonishing success of these concepts in their biological counterparts. Despite this deferent approach, we can merely be seen as optimization methods, which are used in a wide range of applications. “Genetic algorithms (GA) are good at taking large, potentially huge search spaces and navigating them, looking for optimal combinations of things, solutions you would find difficult to accomplish.” A genetic algorithm (GA) is an iterative search, optimization and adaptive machine learning technique premised on the principles of Natural selection. They are capable to finding solution to NP hard Problems. Genetic Algorithm based learning has promisingly showed results to a vast variety of function and problems. Travelling Salesman Problem, Tabu Search, and Transportation Problem is such classical problems for computation. This paper represents how to find optimal solution using various method of genetic algorithm. Advantages and disadvantages of this algorithm are reported and discussed.
关键词：Crossover; Genetic Algorithm; Mutation; Random;Population