Add to ORKGThe Travelling Salesman Problem (TSP) is one of the hardest and the most fundamental problems in Computer Science. Although several techniques have been used in the past to reduce the running time of TSP, Genetic algorithms can reduce the running times of NP-complete problems substantially and have the capability of being parallelized. MapReduce is a parallel programming paradigm currently use and Hadoop is one of the most popular MapReduce frameworks because its robust, well designed and scalable file system. In this paper we use a genetic algorithm and parallelizing it on MapReduce Hadoop framework to reduce the running time of Travelling Salesman Problem
The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization probl...
Abstract — Solving NP hard problem like Travelling Salesman Problem (TSP) is a major challenge faced...
For the solution of combinatorial problem, various algorithms has been investigated. However, almost...
This research investigated the application of Genetic Algorithm capable of solving the traveling sal...
The main aim of this thesis is the comparison of parallel and sequential algorithm implementation fo...
Abstract — This paper presents the literature survey review of Travelling Salesman Problem (TSP). TS...
In this paper, software was developed to solve the travelling salesman problem. The Travelling Sales...
Traditional genetic algorithms often meet the occurrence of slow convergence and enclosure competiti...
Abstract: Traveling salesman problem is quite known in the field of combinatorial optimization. Thro...
The Travelling Salesman Problem (TSP) is one of the most widely and deeply studied problems in optim...
Traveling Salesman Problem (TSP) is known as one of the combinatorial optimization problems. The Gen...
This thesis discuss about Genetic Algorithm to solve PCB component placement modeled as Travelling S...
Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Sa...
By introducing the concept of Oracle we propose an approach for improving the performance of genetic...
The well known NP-complete problem of the Traveling Salesman Problem (TSP) is coded in genetic form....
The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization probl...
Abstract — Solving NP hard problem like Travelling Salesman Problem (TSP) is a major challenge faced...
For the solution of combinatorial problem, various algorithms has been investigated. However, almost...
This research investigated the application of Genetic Algorithm capable of solving the traveling sal...
The main aim of this thesis is the comparison of parallel and sequential algorithm implementation fo...
Abstract — This paper presents the literature survey review of Travelling Salesman Problem (TSP). TS...
In this paper, software was developed to solve the travelling salesman problem. The Travelling Sales...
Traditional genetic algorithms often meet the occurrence of slow convergence and enclosure competiti...
Abstract: Traveling salesman problem is quite known in the field of combinatorial optimization. Thro...
The Travelling Salesman Problem (TSP) is one of the most widely and deeply studied problems in optim...
Traveling Salesman Problem (TSP) is known as one of the combinatorial optimization problems. The Gen...
This thesis discuss about Genetic Algorithm to solve PCB component placement modeled as Travelling S...
Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Sa...
By introducing the concept of Oracle we propose an approach for improving the performance of genetic...
The well known NP-complete problem of the Traveling Salesman Problem (TSP) is coded in genetic form....
The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization probl...
Abstract — Solving NP hard problem like Travelling Salesman Problem (TSP) is a major challenge faced...
For the solution of combinatorial problem, various algorithms has been investigated. However, almost...