International Journal of Computational Intelligence Systems

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Volume 9, Issue 2, April 2016, Pages 227 - 244

Stochastic Capacity Acquisition and Allocation Model for Bandwidth Brokers under Fuzzy Volume Based Pricing Scheme

Authors
Hasan Hüseyin Turan1, *, hasan.turan@qu.edu.qa, Nihat Kasap2, nihatk@sabanciuniv.edu, Dursun Delen3, dursun.delen@okstate.edu, Mehmet Nahit Serarslan4, seraslann@itu.edu.tr
1Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar
2Sabanci University, School of Management, Tuzla, 34956, Istanbul, Turkey
3Spears School of Business, Oklahoma State University, Oklahoma, USA
4Istanbul Technical University, Department of Industrial Engineering, Maçka, 34367, Istanbul, Turkey
*Corresponding author: E-mail: hasan.turan@qu.edu.qa; Tel: (+974) 3309-0921; Fax: (+974) 4403-4101.
Corresponding Author
Hasan Hüseyin Turanhasan.turan@qu.edu.qa
Received 8 December 2014, Accepted 1 January 2016, Available Online 1 April 2016.
DOI
10.1080/18756891.2016.1149998How to use a DOI?
Keywords
Telecommunications market; bandwidth broker; fuzzy stochastic mathematical programming; fuzzy VSS and EVPI
Abstract

In this paper, bandwidth acquisition and allocation problem of a telecommunications Bandwidth Broker (BB) is analyzed under uncertain end-user capacity requests and pay-per-byte (volume) based pricing policy. Furthermore, related objective function coefficients such as revenue and costs are modeled as fuzzy numbers in order to cope with vague market conditions. By integrating fuzzy mathematical programming and two-stage stochastic programming techniques, deterministic equivalent of single objective profit maximization problem of BB is obtained solved to optimality. In addition, infrastructure related performance measures such as delay and jitter amounts in the network are modelled via stochastic parameters that obey some known probability distributions. Two performance statistics namely fuzzy Expected Value of Perfect Information (EVPI) and fuzzy Value of Stochastic Solution (VSS) are defined to demonstrate the efficiency of proposed methodology compared to deterministic approach. In addition, several secondary performance measures such as expected capacity utilization, expected demand fulfilment ratio and capacity loss are calculated under different problem settings. In conclusion, numerical experiments showed that fuzzy stochastic method provides more profit depending upon problem size in compression with deterministic strategy.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 2
Pages
227 - 244
Publication Date
2016/04/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1149998How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Hasan Hüseyin Turan
AU  - Nihat Kasap
AU  - Dursun Delen
AU  - Mehmet Nahit Serarslan
PY  - 2016
DA  - 2016/04/01
TI  - Stochastic Capacity Acquisition and Allocation Model for Bandwidth Brokers under Fuzzy Volume Based Pricing Scheme
JO  - International Journal of Computational Intelligence Systems
SP  - 227
EP  - 244
VL  - 9
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1149998
DO  - 10.1080/18756891.2016.1149998
ID  - Turan2016
ER  -