A Hybrid Method for Recommendation Systems based on Tourism with an Evolutionary Algorithm and Topsis Model

• Published in: Fuzzy information and engineering Vol. 14; no. 1; pp. 26 - 50
• Main Authors: Forouzandeh, Saman, Rostami, Mehrdad, Berahmand, Kamal
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.01.2022; Taylor & Francis Group; Tsinghua University Press
• Subjects: ABC algorithm; Algorithms; Decision making; Evolutionary algorithms; Facebook social network; Hybrid systems; Multiple criterion; Recommender systems; Social networks; Swarm intelligence; topsis model; Tourism
• ISSN: 1616-8658; 1616-8666
• DOI: 10.1080/16168658.2021.2019430

Recommender systems have been pervasively applied as a technique of suggesting travel recommendations to tourists. Actually, recommendation systems significantly contribute to the decision-making process of tourists. A new approach of recommendation systems in the tourism industry by a combination of the Artificial Bee Colony (ABC) algorithm and Fuzzy TOPSIS is proposed in the present paper. A multi-criteria decision-making method called the Techniques for Order of Preference by Similarity to Ideal Solution (TOPSIS) has been applied for the purpose of optimizing the system. Data were gathered through a 1015 online questionnaire on the Facebook social media site. In the first stage, the TOPSIS model defines a positive ideal solution in the form of a matrix with four columns, which indicates factors that get involved in this study. In the second stage, the ABC algorithm starts to search amongst destinations and recommends the best tourist spot to users.