Solving Multi Constrained Team orienteering Problems to Generate Tourist Routes

Generating personalized tourist routes based on a tourist’s interests and constraints is an upcoming trend in tourist applications. This problem can be directly related to the Multi Constrained Team Orienteering Problem with Time Windows (MCTOPTW). The MCTOPTW consists of a set of locations, each of them with a certain score, a time window and one or more associated attributes, such as an entrance fee. Each attribute type has an associated constraint with a maximum allowed value for a route, such as a limited budget. Visiting a location within its time window allows collecting its score as a reward. The goal is to determine a fixed number of routes that maximize the collected score without violating any of the constraints. This paper describes an iterated local search metaheuristic to solve the MCTOPTW, in order to generate personalized tourist routes in real-time. Extensive experimental results with new and existing benchmark instances prove the appropriateness of the algorithm.status: publishe