Metaheuristics for tourist trip planning

Abstract

The aim of this paper is to present an overview of metaheuristics used in tourism and to introduce skewed variable neighbourhood search to solve the team orienteering problem (TOP). Selecting the most interesting points of interest and designing a personalised tourist trip, can be modelled as a TOP with time windows (TOPTW). Guided local search (GLS) and variable neighbourhood search (VNS) are applied to efficiently solve the TOP. Iterated local search (ILS) is implemented to solve the TOPTW. The GLS and VNS algorithms are compared with the best known heuristics and applied on large problem sets. The obtained results are almost of the same quality as the results of these heuristics but the computational time is reduced significantly. For some of the problems VNS calculates new best solutions. The results of the ILS algorithm, applied to large problem sets, have an average gap with the optimal solution of only 2.7%, with much less computational effort. © Springer-Verlag Berlin Heidelberg 2009.