Multi-objective Tourist Trip Design Problem in Chiang Mai City

Abstract

This study aims to solve a multi-objective tourist trip design problem (MO-TTDP) in order to simultaneously maximize tourist satisfaction and minimize total traveling cost. The goal is to identify optimal routing for tourist under time window and time horizon constraints. The mathematical model is first presented to find optimal routing under limited budget. However, the exact algorithm cannot find solution with multiple objectives simultaneously. Therefore, this study applies a metaheuristic, called Global Local and Near-Neighbour Particle Swarm Optimization (GLNPSO), to solve the MO-TTDP. Several local search strategies are also proposed to enhance the solution quality. The proposed algorithm is implemented on the real-case study in Chiang Mai City, Thailand. The experimental results show that the proposed algorithm yields a set of diverse and high quality non-dominated solutions.