Open AccessFixed Task Scheduling of Industrial Robot using Genetic Algorithm Based Travelling Salesman Problem
Author(s) -
Sasmita Nayak,
Neeraj Kumar,
B. B. Choudhury
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1595.039520
Subject(s) - travelling salesman problem , shortest path problem , mathematical optimization , computer science , scheduling (production processes) , genetic algorithm , dynamic priority scheduling , job shop scheduling , task (project management) , algorithm , mathematics , theoretical computer science , engineering , graph , routing (electronic design automation) , computer network , quality of service , systems engineering
The task scheduling of any industrial robots is a prior requirement to effectively use the capability by obtaining shortest path with optimum completion time. In this article, we have presented Travelling Salesman Problem (TSP) with Genetic Algorithm (GA) search technique based task scheduling technique for obtaining optimum shortest path of the task.TSP finds an optimal solution to search for the shortest route by considering every location for completing the required tasks by setting up GA. This article embrace the adaption and implementation of the Genetic Algorithm search strategy for the task scheduling problem in the cooperative control of multiple resources for getting shortest path with minimize the completion time for two zone specific task allocation problem. It can be inferred from the simulation results that the Genetic Algorithm search technique can be considered as a viable solution for the task scheduling problem