A STUDY OF TRAVELLING SALESMAN PROBLEM USING REINFORCEMENT LEARNING OVER GENETIC ALGORITHM
Main Article Content
Abstract
This paper represents the applications of Genetic Algorithm (GA) to solve a Travelling Salesman
problem (TSP). TSP is a simple to describe and mathematically well characterized problem but it is quite difficult to solve. This is a NP-hard type problem i.e. this problem is hard as the hardest problem in NPcomplete space. We present the Crossover and Mutation operators, sorting of the solutions to calculate the bestoptimal solutions. Previously, a numerical illustration was used to signify the model with the techniques. This paper employs Reinforcement Learning to solve the Traveling Salesman problem in the mean of Genetic Algorithm. The technique proposes a model (actions, states, reinforcements).
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.