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A survey on algorithmic approaches for solving tourist trip design problems

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Abstract

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 POIs, visiting time required for each POI, POIs visiting days/hours, entrance fees, weather conditions) and respecting the time available for sightseeing on a daily basis. The aim of this work is to survey models, algorithmic approaches and methodologies concerning tourist trip design problems. Recent approaches are examined, focusing on problem models that best capture a multitude of realistic POIs attributes and user constraints; further, several interesting TTDP variants are investigated. Open issues and promising prospects in tourist trip planning research are also discussed.

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Notes

  1. A problem for which there is a constant \(c\) such that it is NP-hard to find an approximation algorithm with approximation ratio better than \(c\).

  2. Excess of an \(s-t\) path is the difference of the path length from the shortest \(s-t\) path.

  3. Namely, try exhaustive search.

  4. Given an integer \(k\) and a collection of subsets, of a set \(S\), partitioned into groups, pick \(k\) subsets of that collection such that the cardinality of their union is maximized with the restriction that at most one set is picked from each group.

  5. VRP can be described as the problem of designing optimal delivery or collection routes from a depot to a number of nodes subject to certain constraints. The most common constraints are (i) capacity constraints, i.e., a demand is attached to each node and the sum of weights loaded on any route may not exceed the vehicle capacity, (ii) time constraints over individual routes, (iii) time windows, and (iv) precedence relations between pairs of nodes. Most variants of VRP assume that all nodes must be visited and there is no profit collected when visiting a node.

  6. Program Evaluation Review Technique.

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Acknowledgments

We sincerely thank the anonymous referees for their constructive comments which considerably contributed to improving the presentation and structure of our article. This work has been supported by the EU FP7/2007-2013 (DG CONNECT.H5-Smart Cities and Sustainability), under Grant agreement no. 288094 (project eCOMPASS).

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Authors and Affiliations

  1. Department of Cultural Technology and Communication, University of the Aegean, Mytilene, Greece

    Damianos Gavalas

  2. Computer Technology Institute and Press ‘Diophantus’ (CTI), Patras, Greece

    Damianos Gavalas, Charalampos Konstantopoulos, Konstantinos Mastakas & Grammati Pantziou

  3. Department of Informatics, University of Piraeus, Piraeus, Greece

    Charalampos Konstantopoulos

  4. Department of Mathematics, University of Athens, Athens, Greece

    Konstantinos Mastakas

  5. Department of Informatics, Technological Educational Institution of Athens, Athens, Greece

    Grammati Pantziou

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  1. Damianos Gavalas
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  2. Charalampos Konstantopoulos
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  4. Grammati Pantziou
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Correspondence to Damianos Gavalas.

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Gavalas, D., Konstantopoulos, C., Mastakas, K. et al. A survey on algorithmic approaches for solving tourist trip design problems. J Heuristics 20, 291–328 (2014). https://doi.org/10.1007/s10732-014-9242-5

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