Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?

K. Gkiotsalitis; A. Stathopoulos

doi:10.1007/978-3-319-18320-6_4

Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?

K. Gkiotsalitis, A. Stathopoulos^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.

Original language	English
Title of host publication	Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis
Editors	Manolis Papadrakakis, Nikos D. Lagaros
Publisher	Springer
Pages	53-71
Number of pages	19
ISBN (Print)	9783319183190
DOIs	https://doi.org/10.1007/978-3-319-18320-6_4
Publication status	Published - 22 May 2015
Externally published	Yes
Event	1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014: Dedicated to the Memory of Professor M.G. Karlaftis - Kos, Greece Duration: 4 Jun 2014 → 6 Jun 2014 Conference number: 1

Publication series

Name	Computational Methods in Applied Sciences
Volume	38
ISSN (Print)	1871-3033

Conference

Conference	1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014
Abbreviated title	OPT-I 2014
Country/Territory	Greece
City	Kos
Period	4/06/14 → 6/06/14

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10.1007/978-3-319-18320-6_4

Cite this

Gkiotsalitis, K., & Stathopoulos, A. (2015). Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? In M. Papadrakakis, & N. D. Lagaros (Eds.), Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis (pp. 53-71). (Computational Methods in Applied Sciences; Vol. 38). Springer. https://doi.org/10.1007/978-3-319-18320-6_4

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title = "Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?",

abstract = "Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.",

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note = "1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 : Dedicated to the Memory of Professor M.G. Karlaftis, OPT-I 2014 ; Conference date: 04-06-2014 Through 06-06-2014",

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Gkiotsalitis, K & Stathopoulos, A 2015, Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? in M Papadrakakis & ND Lagaros (eds), Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. Computational Methods in Applied Sciences, vol. 38, Springer, pp. 53-71, 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014, Kos, Greece, 4/06/14. https://doi.org/10.1007/978-3-319-18320-6_4

Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? / Gkiotsalitis, K.; Stathopoulos, A.
Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. ed. / Manolis Papadrakakis; Nikos D. Lagaros. Springer, 2015. p. 53-71 (Computational Methods in Applied Sciences; Vol. 38).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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PY - 2015/5/22

Y1 - 2015/5/22

N2 - Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.

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Gkiotsalitis K, Stathopoulos A. Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? In Papadrakakis M, Lagaros ND, editors, Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. Springer. 2015. p. 53-71. (Computational Methods in Applied Sciences). doi: 10.1007/978-3-319-18320-6_4

Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?

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