Solving NP-Complete Problems Using Genetic Algorithms

被引：10
|
作者：
Arabi, Bander Hassan [1 ]
机构：
[1] King Abdulaziz Univ, Dept Res & Dev, Distance Learning, POB 80254, Jeddah, Saudi Arabia
来源：
2016 UKSIM-AMSS 18TH INTERNATIONAL CONFERENCE ON COMPUTER MODELLING AND SIMULATION (UKSIM) | 2016年
关键词：
component; NP-Complet Problem; Genetic Algorithm; Traveling Salesman Problem;
D O I：
10.1109/UKSim.2016.65
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Genetic Algorithms are designed to find the accuracy of approximated solutions in order to perform as effectively as possible. This paper present a new way for genetic algorithm to solve NP-Complete problem. We study genetic algorithm to find an optimal solution for instances of the Traveling Salesman Problem. To overcome this solution, we have to see what is the shortest path that satisfies all of these conditions? We review the paradigms of design of genetic algorithm and demonstrate how they can be applied for the Traveling Salesman Problem. The experiments are presented in which the performance of genetic algorithm is compared to that of Exhaustive Searches.
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页码：43 / 48
页数：6
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