Restructuring parcel delivery network by considering dynamic customer demand

dc.contributor.authorJin, Hyun-Woong
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2018-06-28
dc.date.available2018-06-28
dc.date.issued2018-06-28
dc.description.abstractParcel delivery service is one of the fastest growing industries in the world as the e-commerce such as online shopping mall expands rapidly. To increase its market share, most of parcel delivery service companies construct their delivery network as a form of hub-spoke network which is known to be efficient to deliver large scale products through widely spread area. In hub-spoke network, the number of hubs and their locations are important decision issues. Even though there are many researches on the hub-spoke network design, there is a lack of researches which deal with the fluctuating customer demand. Moreover, all the previous researches considering the fluctuating customer demand assumed that the capacity of hub facility is unlimited. Therefore, this research aims to propose the restructuring procedure of the parcel delivery network by considering the fluctuating customer demand with the capacitated hub facilities. In this research, utilization of temporary hubs is proposed so as to satisfy the fluctuating customer demand. Temporary hub responds to the excessive demands assigned to the permanent hubs and it is closed during the recession period to reduce its operating cost. A nonlinear integer programming model is constructed to decide the number of temporary hubs and their location at each time period. Since the complexity of the constructed mathematical model is NP-hard, GRASP based heuristic solution procedure is proposed. To evaluate the appropriateness of the proposed algorithm, experimental test with various demand sets considering four design factors are performed and the performance of the proposed algorithm is compared with the existing meta-heuristic algorithm. Test results show that the algorithm proposed in this research is more robust than the existing algorithm against the fluctuation of customer demand as well as it provides overall better results.en
dc.formattext
dc.format.extent14 strancs
dc.identifier.doi10.15240/tul/001/2018-2-006
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/26416
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.ispartofBowen, J. (2012). A spatial analysis of FedEx and UPS: hubs, spokes, and network structure. Journal of Transport Geography, 24(2), 419-431. https://dx.doi.org/10.1016/j.jtrangeo.2012.04.017.cs
dc.relation.ispartofCampbell, J. F. (1990). Locating transportation terminals to serve an expanding demand. Transportation Research Part B, 24(3), 173-192. https://dx.doi.org/10.1016/0191-2615(90)90015-Q.cs
dc.relation.ispartofCheung, W., Leung, L. C., & Wong, Y. M. (2001). Strategic service network design for DHL Hong Kong. Interfaces, 31(4), 1-14. https://dx.doi.org/10.1287/inte.31.4.1.9663.cs
dc.relation.ispartofContreras, I., Cordeau, J., & Laporte, G. (2011). The dynamic uncapacitated hub location problem. Transportation Science, 45(1), 18-32. https://dx.doi.org/10.1287/trsc.1100.0326.cs
dc.relation.ispartofDucret, R. (2014). Parcel deliveries and urban logistics: Changes and challenges in the courier express and parcel sector in Europe – The French case. Research in Transportation Business & Management, 11(10), 1274-1280. https://dx.doi.org/10.1016/j.rtbm.2014.06.009.cs
dc.relation.ispartofEbrahimi-Zade, A., Hosseini-Nasab, H., Zare-Mehrjerdi, Y., & Zahmatkesh, A. (2016) Multi-period hub set covering problems with flexible radius: A modified genetic solution. Applied Mathematical Modelling, 40(4), 2968-2982. https://dx.doi.org/10.1016/j.apm.2015.09.064.cs
dc.relation.ispartofFarahani, R. Z., Hekmatfar, M., Arabani, A. B., & Nikbakhsh, E. (2013). Hub location problems: A review of models, classification, solution techniques, and applications. Computers & Industrial Engineering, 64(4), 1096-1109. https://dx.doi.org/10.1016/j.cie.2013.01.012.cs
dc.relation.ispartofFeo, T., & Resende, M. (1995). Greedy randomized adaptive search procedures. Journal of Global Optimization, 6(2), 109-133. https://dx.doi.org/10.1007/BF01096763.cs
dc.relation.ispartofGelareh, S., Monemi, R. N., & Nickel, S. (2015). Multi-period hub location problems in transportation. Transportation Research Part E, 75(1), 67-94. https://dx.doi.org/10.1016/j.tre.2014.12.016.cs
dc.relation.ispartofGlover, F. (1989). Tabu Search-Part I. ORSA Journal on Computing, 1(3), 190-206. https://dx.doi.org/10.1287/ijoc.1.3.190.cs
dc.relation.ispartofHayashi, K., Nemoto, T., & Nakaharai, S. (2014). The Development of the Parcel Delivery Service and its Regulations in China. Procedia – Social and Behavioral Sciences, 125(20), 186-198. https://dx.doi.org/10.1016/j.sbspro.2014.01.1466.cs
dc.relation.ispartofHertz, A., & Widmer, M. (2003). Guidelines for the use of meta-heuristics in combinatorial optimization. European Journal of Operational Research, 151(2), 247-252. https://dx.doi.org/10.1016/S0377-2217(02)00823-8.cs
dc.relation.ispartofJo, Y., Park, D., & Park, H. (2012). A study on network optimization of parcel service industry. The Korea Spatial Planning Review, 72(3), 102-120.cs
dc.relation.ispartofJung, H., Lee, K., & Chun, W. (2006). Integration of GIS, GPS, and optimization technologies for the effective control of parcel delivery service. Computers & Industrial Engineering, 51(1), 154-162. https://dx.doi.org/10.1016/j.cie.2006.07.007.cs
dc.relation.ispartofJung, S. Y., & Kim, S. M. (2015). MADM Analysis based optimal decision making methodology for location selection of parcel terminal. Journal of the Korean Society of Supply Chain Management, 15(1), 83-92.cs
dc.relation.ispartofKim, T., Hwang, S., & Jung, Y. (2015). A study of supply chain design for point to point distribution network in logistics service industry. DAEHAN Association of Business Administration, 28(2), 735-747.cs
dc.relation.ispartofLee, Y. S., Kim, M. Y., Kim, S. T., & Lee, Y. H. (2005). A study on supply chain network design of small package delivery service. Journal of the Korean Society of Supply Chain Management, 5(2), 43-52.cs
dc.relation.ispartofSung, C. S., & Jin, H. W. (2001). Dual-based approach for a hub network design problem under non-restrictive policy. European Journal of Operational Research, 132(1), 88-105. https://dx.doi.org/10.1016/S0377-2217(00)00114-4.cs
dc.relation.ispartofWasner, M., & Zapfel, G. (2004). An integrated multi-depot hub-location vehicle routing model for network planning of parcel service. International Journal of Production Economics, 90(3), 403-419. https://dx.doi.org/10.1016/j.ijpe.2003.12.002.cs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectparcel delivery serviceen
dc.subjectnetwork designen
dc.subjectmeta-heuristicsen
dc.subjectGRASPen
dc.subject.classificationM10
dc.subject.classificationM110
dc.subject.classificationC00
dc.titleRestructuring parcel delivery network by considering dynamic customer demanden
dc.typeArticleen
local.accessopen
local.citation.epage96
local.citation.spage83
local.facultyFaculty of Economics
local.filenameEM_2_2018_06
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue2
local.relation.volume21
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