Tour Multi-Route Planning With Matrix-Based Differential Evolution

Abstract

Tourism is an important industry sector that requires tour companies to plan multiple routes for different tour groups, which is called tour multi-route planning. This paper focuses on tour multi-route planning, which can improve the economic benefit and allocation efficiency of tour resources. The main contributions of this paper are threefold. First, we propose a novel multiple routes planning model that captures the real-world tourism scenario and practical constraints. We also define four typical constraints for tourism planning and classify them into soft and hard constraints. Second, we develop a matrix-based differential evolution algorithm to jointly optimize multiple routes that can efficiently handle the high-dimensional optimization under various constraints. Third, we collect real-world data to construct problem instances and compare the performance of our algorithm with the conventional differential evolution algorithms in terms of runtimes. The experimental results show that our algorithm can effectively solve tour multi-route planning problems and achieve excellent runtimes performance, suitable for large-scale transportation network optimization.