Coyote Optimization and MILP for Multi-Destination Travel Planning in Indonesia

Indah Citra Sakinah, a Master’s student under the Faculty of Data Science and Computing (FSDK) and a researcher at the Institute for Artificial Intelligence and Big Data (AIBIG), is conducting research in Artificial Intelligence and tourism. Originally from Riau, Indonesia, she holds a bachelor’s degree in informatics engineering from Universitas Muhammadiyah Riau (UMRI). Her research focuses on developing an optimization algorithm based on the Coyote Optimization Algorithm (COA) to enhance the performance of travel recommendation systems.

One of the main challenges in travel recommendation systems is data scarcity and the difficulty of optimally tailoring recommendations to tourist preferences. To address this issue, this study integrates the COA optimization approach in modelling tourist destination recommendations, aiming to improve the accuracy, relevance and efficiency of the recommendation system.

In addition, this study explores the application of a hybrid optimization method with chaotic maps, designed to enhance exploration and exploitation in the COA algorithm. This approach allows the recommendation system to be more adaptive in responding to changes in tourist preferences and capable of providing more personalized and accurate recommendations based on historical data and current tourism trends.

To overcome the limitations of traditional recommendation models, this study also compares the effectiveness of the original COA with an improved COA version and several other optimization algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA). This comparison aims to provide a clearer understanding of the strengths and weaknesses of each algorithm in supporting multi-destination travel recommendation systems.

Through this innovative approach, this research has the potential to contribute to the development of a more effective tourism recommendation system while strengthening the role of metaheuristic optimization in supporting the data-driven and AI-powered tourism industry. With high enthusiasm and dedication, Indah Citra Sakinah believes that perseverance in research will not only create an academic impact but also pave the way for technological advancements in the tourism sector. Every challenge in research is a step towards success, and the determination to keep moving forward is the key to achieving a greater impact in the field of data science and artificial intelligence.