Harmony search for generalized orienteering problem: best touring in China

Abstract. In order to overcome the drawbacks of mathematical optimization techniques, soft computing algorithms have been vigorously introduced during the past decade. However, there are still some possibilities of devising new al-gorithms based on analogies with natural phenomena. A nature-inspired algo-rithm, mimicking the improvisation process of music players, has been recently developed and named Harmony Search (HS). The algorithm has been success-fully applied to various engineering optimization problems. In this paper, the HS was applied to a TSP-like NP-hard Generalized Orienteering Problem (GOP) which is to find the utmost route under the total distance limit while sat-isfying multiple goals. Example area of the GOP is eastern part of China. The results of HS showed that the algorithm could find good solutions when com-pared to those of artificial neural network.