Solving the tourist trip planning problem with attraction patterns using meta-heuristic techniques

Abstract

The Tourist Trip Design Problem (TTDP) is a challenging task that involves designing an optimal travel itinerary for a tourist visiting multiple Points of Interest (POIs) within a specific city or region, while considering budget, time constraints, and multiple knapsack constraints. To create a customized itinerary that maximizes enjoyment and minimizes travel costs, factors such as POI distance, attractions, categories of POIs, and the tourist’s preferences must be considered. This paper introduces a local search technique for an extended variant of TTDP that includes pattern sequence for POI categories, recently defined by our team. Our approach builds upon existing state-of-the-art solvers based on ILS for the Multi Constrained Team Orienteering Problem with Time Windows (MCTOPTW) variant. The approach has been put to the test and proved its worth by generating high-quality solutions, comparable to the state-of-the-art solvers for simpler variants of TTDP. A test set of 146 instances was used to demonstrate the approach’s effectiveness.