Ant Colony Optimization for Route Planning of Multiple Tourists

초록

This paper builds a Multiple Tourists Route Planning (MTRP) model by incorporating the traveling cost between scenic spots and the ticket fees of the scenic spots along with the budgets of tourists. The aim of this model is to identify optimal routes for multiple tourists that maximize the traveling experience scores of the multiple tourists and at the same time minimize their traveling experience differences under the given budgets. To effectively solve this problem, this paper adapts the five classical ACOs, namely Ant System (AS), Elitist AS (EAS), Rank-based AS (AS(rank)), Min-Max AS (MMAS), and Ant Colony System (ACS) by introducing a new route construction method based on scenic spot pre-selection. Further, a new local search strategy incorporating 2-opt and scenic spot insertion is designed to refine the quality of the found multiple routes. Abundant experiments have been executed on various MTRP instances with different numbers of scenic spots and different numbers of tourists along with different settings of the budgets. The experimental results reveal that the five adapted ACOs are very promising for solving the new MTRP problem and among them. ACS comprehensively performs the best.

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