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New multi-objective optimization model for tourism systems with fuzzy data and new algorithm for solving this model

Author

Listed:
  • Gholamreza Shojatalab

    (University of Mazandaran)

  • Seyed Hadi Nasseri

    (University of Mazandaran)

  • Iraj Mahdavi

    (Mazandaran University of Science and Technology)

Abstract

Tourism is one of the fastest-growing industries in the world and the most significant service sector industry. A fundamental question that can be prompted is how to minimize the total tour cost and, at the same time, design the tour to make the tourists get maximum satisfaction. This paper proposes a new multi-objective optimization model for tourism systems. We have considered problem modelling in the form of multi-objective optimization in which we can optimize the conflicting goals at the same time. Here we have considered a provider of tour packages that intends to minimize its total costs and, at the same time, maximize the satisfaction of tourists with their packages. In our proposed model, some of the model parameters are fuzzy numbers, so an appropriate algorithm is proposed to solve the multi-objective optimization model. The results can offer constructive suggestions on how to design tours on the part of tourism enterprises and choose a proper tour. The main advantage of this study is to consider the problem of optimizing tourism systems in the form of a multi-objective optimization problem that uses both fuzzy and non-fuzzy numbers at the same time. Also, to deal with this specific multi-objective optimization model, a new algorithm based on the Epsilon constraint method is proposed. The proposed algorithm is used in a case study, and in this example, it performed better than the other algorithms.

Suggested Citation

  • Gholamreza Shojatalab & Seyed Hadi Nasseri & Iraj Mahdavi, 2022. "New multi-objective optimization model for tourism systems with fuzzy data and new algorithm for solving this model," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1018-1037, September.
    • Handle: RePEc:spr:opsear:v:59:y:2022:i:3:d:10.1007_s12597-022-00591-3
    DOI: 10.1007/s12597-022-00591-3
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    References listed on IDEAS

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    1. Calver, Stephen J. & Page, Stephen J., 2013. "Enlightened hedonism: Exploring the relationship of service value, visitor knowledge and interest, to visitor enjoyment at heritage attractions," Tourism Management, Elsevier, vol. 39(C), pages 23-36.
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    5. Armin Mahmoudi & Leila Hashemi & Milad Jasemi & James Pope, 2021. "A comparison on particle swarm optimization and genetic algorithm performances in deriving the efficient frontier of stocks portfolios based on a mean‐lower partial moment model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5659-5665, October.
    6. Mahsa Parsaei Motamed & Shahrooz Bamdad, 2022. "A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 266-303, March.
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    Cited by:

    1. Skare, Marinko & Gavurova, Beata & Polishchuk, Volodymyr & Nawazish, Mirza, 2023. "A fuzzy model for evaluating the level of satisfaction of tourists regarding accommodation establishments according to social class on the example of V4 countries," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    2. K. Kapil Raj & S. Srinivasan & C. D. Nandakumar, 2023. "Efficiency analysis of reinsurers in India: a three stage fuzzy closed system DEA approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1179-1201, September.
    3. Gholamreza Shojatalab & Seyed Hadi Nasseri & Iraj Mahdavi, 2023. "New multi-objective optimization model for tourism systems with fuzzy data and new approach developed epsilon constraint method," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1360-1385, September.

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