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Extended hypercube queueing models for stochastic facility location problems

Research output: Contribution to conference - Without ISBN/ISSN › Abstract

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Standard

Extended hypercube queueing models for stochastic facility location problems. / Boyacı, Burak; Geroliminis, Nikolas.
2012. Abstract from EURO XXV, Vilnius, Lithuania.

Research output: Contribution to conference - Without ISBN/ISSN › Abstract

Harvard

Boyacı, B & Geroliminis, N 2012, 'Extended hypercube queueing models for stochastic facility location problems', EURO XXV, Vilnius, Lithuania, 8/07/12 - 11/07/12.

APA

Boyacı, B., & Geroliminis, N. (2012). Extended hypercube queueing models for stochastic facility location problems. Abstract from EURO XXV, Vilnius, Lithuania.

Vancouver

Boyacı B, Geroliminis N. Extended hypercube queueing models for stochastic facility location problems. 2012. Abstract from EURO XXV, Vilnius, Lithuania.

Author

Boyacı, Burak ; Geroliminis, Nikolas. / Extended hypercube queueing models for stochastic facility location problems. Abstract from EURO XXV, Vilnius, Lithuania.

Bibtex

@conference{dc31516e9ee64a6fb89783422a6ef0a1,
title = "Extended hypercube queueing models for stochastic facility location problems",
abstract = "In this research, we are modeling the facility location problem for systems with many servers and stochastic demand, such as emergency response and on-demand transportation systems, by using spatial queues,specifically hypercube queuing models (HQMs). We are proposing two extended HQMs and a heuristic method which uses an approach similar to dynamic programming. Briefly, the heuristic solves a subproblem for each sub region which is generated by using similarities in demand and then combines them accordingly. Preliminary analysis gives promising results for some real life instances.",
author = "Burak Boyacı and Nikolas Geroliminis",
year = "2012",
month = jul,
day = "8",
language = "English",
note = "EURO XXV ; Conference date: 08-07-2012 Through 11-07-2012",

}

RIS

TY - CONF

T1 - Extended hypercube queueing models for stochastic facility location problems

AU - Boyacı, Burak

AU - Geroliminis, Nikolas

PY - 2012/7/8

Y1 - 2012/7/8

N2 - In this research, we are modeling the facility location problem for systems with many servers and stochastic demand, such as emergency response and on-demand transportation systems, by using spatial queues,specifically hypercube queuing models (HQMs). We are proposing two extended HQMs and a heuristic method which uses an approach similar to dynamic programming. Briefly, the heuristic solves a subproblem for each sub region which is generated by using similarities in demand and then combines them accordingly. Preliminary analysis gives promising results for some real life instances.

AB - In this research, we are modeling the facility location problem for systems with many servers and stochastic demand, such as emergency response and on-demand transportation systems, by using spatial queues,specifically hypercube queuing models (HQMs). We are proposing two extended HQMs and a heuristic method which uses an approach similar to dynamic programming. Briefly, the heuristic solves a subproblem for each sub region which is generated by using similarities in demand and then combines them accordingly. Preliminary analysis gives promising results for some real life instances.

M3 - Abstract

T2 - EURO XXV

Y2 - 8 July 2012 through 11 July 2012

ER -