A survey on algorithmic approaches for solving tourist trip design problems

  title={A survey on algorithmic approaches for solving tourist trip design problems},
  author={Damianos Gavalas and Charalampos Konstantopoulos and Konstantinos Mastakas and G. Pantziou},
  journal={Journal of Heuristics},
The tourist trip design problem (TTDP) refers to a route-planning problem for tourists interested in visiting multiple points of interest (POIs). TTDP solvers derive daily tourist tours, i.e., ordered visits to POIs, which respect tourist constraints and POIs attributes. The main objective of the problem discussed is to select POIs that match tourist preferences, thereby maximizing tourist satisfaction, while taking into account a multitude of parameters and constraints (e.g., distances among… 

Solving Tourist Trip Design Problems from a User's Perspective

  • W. Wörndl
  • Computer Science
    Mensch & Computer Workshopband
  • 2016
This position paper briefly motivates an abstract model for tourist trip design problems and outlines two scenarios we are working on: 1. a city trip planner to recommend a sequence of items for

Time-Dependent Tourist Tour Planning with Adjustable Profits

A problem-specific preprocessing step is proposed which enables fast heuristic (iterated local search) and exact (mixed-integer linear programming) personalized trip-planning for tourists.

Improving Itinerary Recommendations for Tourists Through Metaheuristic Algorithms: An Optimization Proposal

This research presents a mobile recommender system based on Tourist Trip Design Problem (TTDP)/Time Depending (TD) – Orienteering Problem (OP) – Time Windows (TW), which analyzes in real time the user’s constraints and the points of interest's constraints and offers real-time recommendations.

Recommending a sequence of interesting places for tourist trips

It is shown that Dijkstra’s algorithm can be modified to find not only the shortest paths, but also trips that solve the TTDP by maximizing the entertainment for the user while respecting time and budget constraints.

Planning the trip itinerary for tourist groups

This paper introduces a new problem, as an extension of the existing problem in the literature that is used for planning the trip of a single tourist, and designs a new algorithm based on tabu search metaheuristic that uses two new unique operators for exploring the search space.



A Tabu Search approach for Multi Constrained Team Orienteering Problem and its application in touristic trip planning

This paper proposes a Tabu Search approach for solving the MCTOPTW problem, which employs a tabu list, a perturbation and a diversification mechanism, and its performance is compared to the state of the art results.

Cluster-Based Heuristics for the Team Orienteering Problem with Time Windows

Two cluster-based extensions to ILS are proposed addressing the aforementioned weakness of ILS by grouping POIs on disjoint clusters (based on geographical criteria), thereby making visits to such POIs more attractive.

Efficient Heuristics for the Time Dependent Team Orienteering Problem with Time Windows

Two efficient cluster-based heuristics for the TDTOPTW which yield high quality solutions, take into account time dependency in calculating travel times between POIs and make no assumption on periodic service schedules are proposed.

Tourist Trip Planning Functionalities: State-of-the-Art and Future

Using the Orienteering Problem (OP) and its extensions to model the tourist trip planning problem, allows to deal with a vast number of practical planning problems.


There are many studies which consider an optimal tour on a given graph including the well-known Traveling Salesman Problem (TSP) and Vehicle Routing Problem (VRP). Most of these studies, however,

Time-dependent personal tour planning and scheduling in metropolises

An Optimal Algorithm for the Orienteering Tour Problem

An optimal algorithm is developed to solve the orienteering problem, using Lagrangean relaxation within a branch-and-bound framework, and is solved by a degree-constrained spanning tree procedure.