A NEW HYBRID APPROACH TO TRAVELLING SALESMAN PROBLEM BY REINFORCEMENT LEARNING AND IMPROVEMENT BY TWO-OPT ALGORITHM

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DC Field	Value	Language
dc.contributor.author	Brindha T	-
dc.contributor.author	Saurabhee, Sakthivel	-
dc.date.accessioned	2023-09-07T07:23:08Z	-
dc.date.available	2023-09-07T07:23:08Z	-
dc.date.issued	2023-03-30	-
dc.identifier.issn	1533 -9211	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/3503	-
dc.description.abstract	Travelling Salesman Problem is a well-known problem in combinatorial optimization theory that is still being extensively studied up to date. Various approaches have been analyzed and developed to find an optimal solution to this problem. This paper focuses on a new hybrid approach to the Travelling Salesman Problem using Reinforcement Learning and its improvement by Two-Opt algorithm. The proposed algorithm has been applied to three real world problems, which are the three South Indian states namely, Tamil Nadu, Kerala and Andhra Pradesh which has 32, 16 and 27 cities respectively. The proposed algorithm is also compared to the classical algorithms, especially the Two- Opt algorithm to analyse and find the best of the two given here	en_US
dc.language.iso	en_US	en_US
dc.publisher	The Seybold Report	en_US
dc.subject	TSP	en_US
dc.subject	Hybrid Approach	en_US
dc.subject	Reinforcement Learning	en_US
dc.subject	Two-Opt	en_US
dc.subject	RL and Improvement by Two-Opt	en_US
dc.title	A NEW HYBRID APPROACH TO TRAVELLING SALESMAN PROBLEM BY REINFORCEMENT LEARNING AND IMPROVEMENT BY TWO-OPT ALGORITHM	en_US
dc.type	Article	en_US
Appears in Collections:	National Journals

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