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Enhancing the Sustainability of a Location-Aware Service through Optimization

Author

Listed:
  • Horng-Ren Tsai

    (Department of Information Technology, Lingtung University, No. 1, Lingtung Rd, Taichung City 408, Taiwan)

  • Toly Chen

    (Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100, Wenhua Rd, Taichung City 407, Taiwan)

Abstract

A location-aware service (LAS) is an imperative topic in ambient intelligence; an LAS recommends suitable utilities to a user based on the user’s location and context. However, current LASs have several problems, and most of these services do not last. This study proposes an optimization-based approach for enhancing the sustainability of an LAS. In this paper, problems related to optimizing a LAS system are presented. The distinct nature of a LAS optimization problem in comparison with traditional optimization problems is subsequently described. Existing methods applicable to solving a LAS optimization problem are also reviewed. The advantages and disadvantages of each method are then discussed as a motive for combining multiple optimization methods in this study, as illustrated by an example. Finally, opportunities and challenges faced by researchers in this field are presented.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:12:p:9441-9455:d:43691
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    Citations

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    Cited by:

    1. Jonghyuk Kim & Hyunwoo Hwangbo & Sung Jun Kim & Soyean Kim, 2019. "Location-Based Tracking Data and Customer Movement Pattern Analysis for Sustainable Fashion Business," Sustainability, MDPI, vol. 11(22), pages 1-17, November.
    2. 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.
    3. Sung Hee Jang & Chang Won Lee, 2018. "The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    4. Min-Chi Chiu & Tin-Chih Toly Chen & Keng-Wei Hsu, 2020. "Modeling an Uncertain Productivity Learning Process Using an Interval Fuzzy Methodology," Mathematics, MDPI, vol. 8(6), pages 1-18, June.
    5. 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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