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Design of diversified package tours for the digital travel industry : A branch-cut-and-price approach

Zhao, Yanlu; Alfandari, Laurent

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Authors

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Yanlu Zhao yanlu.zhao@durham.ac.uk
Assistant Professor

Laurent Alfandari



Abstract

Motivated by the revolution brought by the internet and communication technology in daily life, this paper examines how the online travel agencies (OTA) can use these technologies to improve customer value. We consider the design of a fixed number of package tours offered to customers in the digital travel industry. This can be formulated as a Team Orienteering Problem (TOP) with restrictions on budget and time. Different from the classical TOP, our work is the first one to introduce controlled diversity between tours. This enables the OTA to offer tourists a diversified portfolio of tour packages for a given period of time, each potential customer choosing a single tour in the selected set, rather than multiple independent tours over several periods as in the classical TOP. Tuning the similarity parameter between tours enables to manage the trade-off between individual preferences in consumers’ choices and economies of scale in agencies’ bargaining power. We propose compact and extended formulations and solve the master problem by a branch-and-price method, and an alternative branch-cut-and-price method. The latter uses a delayed dominance rule in the shortest path pricing problem solved by dynamic programming. Our methods are tested over benchmark TOP instances of the literature, and a real dataset collected from a Chinese OTA. We explore the impact of tours diversity on all stakeholders, and assess the computational performance of various approaches.

Citation

Zhao, Y., & Alfandari, L. (2020). Design of diversified package tours for the digital travel industry : A branch-cut-and-price approach. European Journal of Operational Research, 285(3), 825-843. https://doi.org/10.1016/j.ejor.2020.02.020

Journal Article Type Article
Acceptance Date Feb 10, 2020
Online Publication Date Feb 14, 2020
Publication Date 2020-09
Deposit Date Sep 2, 2020
Publicly Available Date Feb 14, 2022
Journal European Journal of Operational Research
Print ISSN 0377-2217
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 285
Issue 3
Pages 825-843
DOI https://doi.org/10.1016/j.ejor.2020.02.020
Public URL https://durham-repository.worktribe.com/output/1263065

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