Paper Titles

The Need of End-of-Life Vehicles Management System in Malaysia
p.505

Evaluating ARIMA-Neural Network Hybrid Model Performance in Forecasting Stationary Timeseries
p.510

Performance Measurement System for Sustainable Supply Chain Management
p.516

A Hybrid Fuzzy MCDM Approach for Sustainable Third-Party Reverse Logistics Provider Selection
p.521

Probabilistic Formulation for Emergency Facility Location in a Divided Area
p.527

Multi-Floor Facility Layout Improvement Using Systematic Layout Planning
p.532

ANFIS Based Effluent pH Quality Prediction Model for an Activated Sludge Process
p.538

Comparison of ANFIS and Neural Network Direct Inverse Control Applied to Wastewater Treatment System
p.543

Technology Management: Developing an Innovation Model for Research Universities in Malaysia
p.549

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 845Probabilistic Formulation for Emergency Facility...

Probabilistic Formulation for Emergency Facility Location in a Divided Area

Article Preview

Abstract:

Capacitated minimax facility location-allocation (LA) is a type of facility problem which is of prime importance for emergency situation, since it directly affects the service response time to customers. Capacitated minimax LA problem is concerned with locating some new facilities and allocating their capacity to customers when the maximum travelled distance from customers to facilities is minimized. This study involves a fixed line barrier in a region with some border crossings along it which divides the area into two subregions. Although several studies have recently been done on this problem in which the customer locations are known with certainty, much less attention has been devoted to developing a comprehensive mathematical model for the probabilistic extension of customer locations when there are some restrictions in the region. In order to fill this gap, a Mixed Integer Nonlinear Programming (MINLP) model is proposed for facility LA when customer locations are randomly distributed according to a bivariate normal probability distribution. Finally, the BARON solver in the GAMS software is used to solve the model, and a numerical example is provided to demonstrate its efficiency.

You might also be interested in these eBooks

Materials, Industrial, and Manufacturing Engineering Research Advances 1.1

Info:

Periodical:

Advanced Materials Research (Volume 845)

Pages:

527-531

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.845.527

Citation:

Cite this paper

Online since:

December 2013

Authors:

Seyed Ali Mirzapour*, Kuan Yew Wong, Seyedeh Sabereh Hosseini, Saber Shiripour

Keywords:

Border Crossing, Capacitated Facility Location Problem, Optimization, Probabilistic Customer Locations

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

* - Corresponding Author

[1] Weber, A., Theory of the Location of Industries. Über den Standort der Industrien, Tübingen, (1909).

[2] Cooper, L., A random locational equilibrium problem. Journal of Regional Sciences, 1974. 14: pp.47-54.

[3] Katz, I.N. and L. Cooper, An always-convergent numerical scheme for a random locational equilibrium problem. SIAM Journal on numerical analysis, 1974. 11(4): pp.683-692.

DOI: 10.1137/0711055

[4] Averbakh, I. and S. Bereg, Facility location problems with uncertainty on the plane. Discrete Optimization, 2005. 2(1): pp.3-34.

DOI: 10.1016/j.disopt.2004.12.001

[5] Foul, A., A 1-center problem on the plane with uniformly distributed demand points. Operations Research Letters, 2006. 34(3): pp.264-268.

DOI: 10.1016/j.orl.2005.04.011

[6] Durmaz, E., N. Aras, and İ.K. Altinel, Discrete approximation heuristics for the capacitated continuous location–allocation problem with probabilistic customer locations. Computers & Operations Research, 2009. 36(7): pp.2139-2148.

DOI: 10.1016/j.cor.2008.08.003

[7] Mousavi, S.M. and S.T.A. Niaki, Capacitated location allocation problem with stochastic location and fuzzy demand: A hybrid algorithm. Applied Mathematical Modelling, 2013. 37(7): pp.5109-5119.

DOI: 10.1016/j.apm.2012.10.038

[8] Katz, I.N. and L. Cooper, Facility location in the presence of forbidden regions, I: Formulation and the case of Euclidean distance with one forbidden circle. European Journal of Operational Research, 1981. 6: pp.166-173.

DOI: 10.1016/0377-2217(81)90203-4

[9] Klamroth, K., Algebraic properties of location problems with one circular barrier. European Journal of Operational Research, 2004. 154: pp.20-35.

DOI: 10.1016/s0377-2217(02)00800-7

[10] Huang, S., et al., The K-Connection Location Problem in a Plane. Annals of Operations Research, 2005. 136(1): pp.193-209.

[11] Bischoff, M. and K. Klamroth, An efficient solution method for Weber problems with barriers based on genetic algorithms. European Journal Of Operational Research, 2007. 177: pp.22-41.

DOI: 10.1016/j.ejor.2005.10.061

[12] Canbolat, M.S. and G.O. Wesolowsky, The rectilinear distance Weber problem in the presence of a probabilistic line barrier. European Journal of Operational Research, 2010. 202(1): pp.114-121.

DOI: 10.1016/j.ejor.2009.04.023

[13] Canbolat, M.S. and G.O. Wesolowsky, A planar single facility location and border crossing problem. Computers & Operations Research, 2012. 39(12): pp.3156-3165.

DOI: 10.1016/j.cor.2012.04.002

[14] Klamroth K. Planar Weber location problems with line barriers. Optimization 1996; 49(5–6): 517–27.

DOI: 10.1080/02331930108844547

[15] Aly, A.A. and J.A. White, Probabilistic formulations of the multifacility Weber problem. Naval Research Logistics Quarterly, 1978. 25(3): pp.531-547.

DOI: 10.1002/nav.3800250313