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Integer nonlinear programming and optimized weighted-average approach for mobile hotel recommendation by considering travelers’ unknown preferences

Author

Listed:
  • Yu-Cheng Lin

    (Overseas Chinese University)

  • Toly Chen

    (National Chiao Tung University)

  • Li-Chih Wang

    (Tunghai University)

Abstract

The existing mobile hotel recommendation systems are usually subject to a difficult problem—travelers choose dominated hotels. This problem is difficult to resolve because there is no reason to recommend a hotel that is inferior to another in all aspects. To address this problem, an artificial dimension is added to each hotel to model unknown personal preferences. The possible values along the artificial dimension and the weight associated with it are derived by solving an integer nonlinear programming problem. Thus, the proposed methodology hybridizes objective and subjective weights. An illustrative example is provided to show the applicability of the proposed methodology. In addition, a field study was conducted in a small region of Seatwen District, Taichung City, Taiwan to evaluate the possible advantages of the proposed methodology over existing methods. The experimental results showed that the proposed methodology outperformed five existing methods in improving the successful recommendation rate, with the most significant advantage being up to 33 %. Furthermore, the recommendation results generated using the proposed methodology were found to be less risky.

Suggested Citation

  • Yu-Cheng Lin & Toly Chen & Li-Chih Wang, 2018. "Integer nonlinear programming and optimized weighted-average approach for mobile hotel recommendation by considering travelers’ unknown preferences," Operational Research, Springer, vol. 18(3), pages 625-643, October.
  • Handle: RePEc:spr:operea:v:18:y:2018:i:3:d:10.1007_s12351-016-0270-9
    DOI: 10.1007/s12351-016-0270-9
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    References listed on IDEAS

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    1. Horng-Ren Tsai & Toly Chen, 2014. "Enhancing the Sustainability of a Location-Aware Service through Optimization," Sustainability, MDPI, vol. 6(12), pages 1-15, December.
    2. Chen, Yizeng & Fung, Richard Y.K. & Tang, Jiafu, 2006. "Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1553-1566, November.
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    Cited by:

    1. K. Coussement & K. W. Bock & S. Geuens, 2022. "A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer," Annals of Operations Research, Springer, vol. 315(2), pages 671-694, August.
    2. Toly Chen, 2021. "A diversified AHP-tree approach for multiple-criteria supplier selection," Computational Management Science, Springer, vol. 18(4), pages 431-453, October.

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