Selection of Optimized Location for Ecoparks Using Ant Colony Optimization

Abstract

Ecoparks are an essential component of any ecotourism project. Such parks are developed to protect, preserve, and manage natural land use and land covers that are necessary for the maintenance of the ecological balance of a region. But ecoparks or ecotourism projects have some drawbacks that make the site-selection procedure one of the major determinants of the success of such project. Pollution, the destruction of habitats of wild animals, disturbance to the daily life of indigenous and native people and an increase in the price of local items are some of the major negative contributions of ecotourism. Thus, such projects must be allowed in sites where disturbance and destruction to the local ecosystem will be minimal. But till now no specific and standard methodology has been proposed for the selection of ecopark sites. The selection of sites is now made based on reports received from experts in the related fields; in addition, sometimes the response from native people is also included in the decision-making process. But such decisions often raise controversies, and accusations of favoritism and illegality are rampant. Because there is no quantifiable methodology of site selection, such tumult as discussed above is quite natural. That is why, the present study tries to formulate a methodology of site selection for ecopark projects that is objective and does not depend on the qualitative ratings of experts. Decisions are made using probabilistic optimization methods like ant colony optimization (ACO) algorithm. The ACO algorithm proposed by Dorigo et al. has resolved many critical decision-making problems like the famous problem of the traveling salesman and other within with satisfactory results.