Abstract
We developed a new model for locating facilities with demand that are originated from both residential areas and from passing by flows. A mixed integer program is proposed with the objective function of maximum the total profit gained by serving both types of customers. Since the problem is NP-hard, greedy heuristic and improved greedy heuristic are proposed. The improved greedy heuristic presented solves the computational experiments with competitive results, while the run time is much less than that of the optimal method. The sensitivity of the optimal locations to the input parameters is analyzed with an example network and the results are reported.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zeng WP, Hodgson MJ, Castoillo I (2009) The pickup problem: consumers’ locational preferences in flow interception. Geogr Anal 41:107–126
Berman O, Krass D (1998) Flow intercepting spatial interaction model: a new approach to optimal location of competitive facilities. Locat Sci 6:41–65
Goodchild MF, Noronha VT (1987) Location–allocation and impulsive shopping the case of gasoline retailing. Spatial analysis and location–allocation models. Van Nostrand Reinhold, New York, pp 121–136
Capar I, Kuby M (2012) An efficient formulation of the flow refueling location model for alternative-fuel stations. IIE Trans 44:622–636
Upchuach C, Kuby M (2010) Comparing the p-median and flow-refueling models for locating alternative-fuel stations. J Transp Geogr 18:750–758
Lim S, Kuby M (2010) Heuristic algorithms for siting alternative-fuel stations using the Flow-Refueling Location Model. Eur J Oper Res 204:51–61
Hodgson MJ (1990) A flow-capturing location-allocation model. Geogr Anal 22:270–279
Berman O, Larson RC, Fouska N (1992) Optimal location of discretionary service facilities. Transp Sci 26:201–211
Hodgson MJ, Rosing KE (1992) A network location-allocation model trading off flow capturing and p-median objectives. Ann Oper Res 40:247–260
Berman O (1997) Deterministic flow-demand location problems. J Oper Res Soc 48:75–81
Erdemir ET, Batta R, Spielman S et al (2008) Location coverage models with demand originating from nodes and paths: application to cellular network design. Eur J Oper Res 190:610–632
Erdemir ET (2008) Location-coverage models: nodal and path demand, multiple-type facilities, unviability of servers. PhD thesis, State University of New York, New York
Mrlaina MW (2003) Initiating hydrogen infrastructures: preliminary analysis of a sufficient number of initial hydrogen stations in the US. Int J Hydrog Energy 28:743–755
Wang YW, Wang CR (2010) Locating passenger vehicle refueling stations. Transp Res E 46:791–801
Lin XS, Zhou J, Lin DX (2006) Applications of Matlab7.0. China Machine Press, Beijing
Acknowledgment
The paper is supported National Natural Science Foundation of China (71102071), the major projects of the National Natural Science Foundation of China (71090404/71090400), and National Natural Science Foundation of China (71002020).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shen, Rl., Huo, Jz., Li, Xf. (2014). Models and Algorithms for Locating Facilities with Hybrid Demand for Service. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40060-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-40060-5_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40059-9
Online ISBN: 978-3-642-40060-5
eBook Packages: Business and EconomicsBusiness and Management (R0)