Tourism route optimization based on improved knowledge ant colony algorithm

Abstract With the rapid development of tourism in economy, popular demand for also increases. Unreasonable distribution arises a series problems such as reduction tourist satisfaction and decrease income attractions. Based on consideration route planning, mathematical model which takes maximization overall all groups objective function is established by taking age preferences tourists, upper limits carrying capacity various routes, etc. constraints. It aims to maximize attractions while improving satisfaction. data travel agency, statistical ideas hierarchical clustering random sampling are utilized process acquired obtain simulation examples article. Aiming at this model, knowledge-based hybrid ant colony algorithm designed. On basis, mechanism bacterial foraging introduced. improves performance avoids generation local optimal solution. At same time, two knowledge models addition improve solution quality algorithm. Typical indicates that improved can find higher efficiency when solving planning problem. The satisfy economic benefit enterprises achieves favorable path optimization effect under different optional thus further verifying liveness model.