Travel Itinerary Planning using Traveling Salesman Problem, K-Means Clustering, and Multithreading Approach

Autor: Saputra, Muhammad Yasin Deru, Huda, Sheila Nurul, Rani, Septia
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: AUTOMATA; Vol 1, No 1 (2020)
ISSN: 2721-1940
Popis: In this paper we proposed an algorithm for arranging travel itinerary using various approaches such as, traveling salesman problem with genetic algorithm, k-means clustering, and multithreading. The algorithm will be applied to develop a web based application which capable of making itinerary planning recommendation. This paper mainly focusing on how the proposed algorithm able to optimize the application in terms of computational proccessing time for the sake of efficiency. To make the itinerary recommendation, travelers must fill the input requirements such as number of days for vacation and list of destionations which they whish to visit. The destinations will first be clustered. Then find the TSP solution for the best route for each cluster. This TSP solution will be the itinerary recommendation.
Databáze: OpenAIRE