Multi-objective Optimization of Eco-tourism Routes Integrating Ecological Value: A Study based on Ant Colony Algorithm

Abstract

This paper introduces a new multi-objective model for eco-tourism route planning that incorporates the assessment of the ecological significance with the standard goals of tourist preference and route length. The paper proposes a new approach to the ACO algorithm to derive Pareto-optimal solution for the eco-tourism problem with multiple objectives. The algorithm uses multiple matrices of pheromones for tracking different goals and objectives and also includes the ecological value through a compounded index that considers aspects of the relative importance of biodiversities, the sensitivity of ecosystems, connectivity of habitats, and other ecological values. Experimental outcomes show that the proposed MOP is 58% more diverse than the SOP in terms of solutions and 43% less sensitive to parameters than the SOP. Pareto-optimal solutions show that high ecological value routes are less attractive as they have 45% fewer attractions but have 75% less negative impact on the environment than high satisfaction routes. The model also determines appropriate size and orientation of routes varying by seasons, which indicates the requirement of appropriate management strategies. The results indicate that intelligent route optimization can produce reasonable amount of ecological gains at the expense of slight tourist satisfaction loss, providing valuable support to the eco-tourism managers in the sustainable destination management.