Abstract
This article proposes a methodology based on continuous approximation to address the common logistics problems of locating warehouses and designing physical distribution strategies for a delivery firm with short and immediate time windows of different urgency (e.g., 1 or 2 h). An objective function is developed that includes the principal cost factors (warehouse rental, transportation, inventory cost, and wages). The methodology was applied to the real case of a company in Santiago, Chile, generating a demand model and an optimal logistics design that produced satisfactory results in terms of optimal warehouse locations and associated costs.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Agatz NAH, Fleischmann M, van Nunen JAEE (2008) E-fulfillment and multi-channel distribution—a review. Eur J Oper Res 187(2):339–356
Agatz NAH, Campbell A, Fleischmann M, Savelsbergh M (2011) Time slot management in attended home delivery. Transp Sci 45(3):435–449
Anderson C (2006) The long tail: why the future of business is selling less of more. Hyperion Books, New York
Balakrishnan A, Ward JE, Wong RT (1987) Integrated facility location and vehicle routing models: recent work and future prospects. Am J Math Manag Sci 7:35–61
Baldacci R, Mingozzi A, Roberti R (2012) Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. Eur J Oper Res 218(2012):1–6
Berning C, Ernst S, Hooker NH (2005) Are e-grocers serving the right markets? Choices 20(1):77–80
Campbell JF (2013) A continuous approximation model for time definite many-to-many transportation. Transp Res Part B Methodol 54:100–112
Campbell A, Savelsbergh M (2005a) Decision support for consumer direct grocery initiatives. Trans Sci 39(3):313–327
Campbell A, Savelsbergh M (2005b) Incentive schemes for attended home delivery services. Trans Sci 40(3):327–341
Clarens G, Hurdle VF (1975) An operating strategy for a commuter bus system. Trans Sci 9:1–20
Cui T, Ouyang Y, Shen ZJ (2010) Reliable facility location under the risk of disruptions. Oper Res 58(4):998–1011
Daganzo CF (1984) The distance traveled to visit N points with a maximum of C stops per vehicle: an analytic model and an application. Trans Sci 18(4):331–350
Daganzo CF (1987a) Modeling distribution problems with time windows: part I. Trans Sci 21:171–179
Daganzo CF (1987b) Modeling distribution problems with time windows: part II: two customer types. Trans Sci 21:180–187
Daganzo CF (1999) Logistics systems analysis. Springer, Heidelberg
Dasci A, Laporte G (2005) A continuous model for multistore competitive location. Oper Res 53(2):263–280
Eilon S, Watson-Gandy CDT, Christofides N (1971) Distribution management: mathematical modelling and practical analysis. Hafner, New York, NY
Erera AL, Savelsbergh MWP, Uyar E (2009) Fixed routes with backup vehicles for stochastic vehicle routing problems with time constraints. Networks 54:270–283
Genta S, Muñoz JC (2007) On assigning drivers for a home-delivery system on a performance basis. Ann Oper Res 155(1):107–117
Huang M, Smilowitz KR, Balcik B (2013) A continuous approximation approach for assessment routing in disaster relief. Transp Res Part B 50(1):20–41
Langevin A, Mbaraga P, Campbell JF (1996) Continuous approximation models in freight distribution: an overview. Trans Res B 30(3):163–188
Laporte G (1988) Location-routing problems. In: Golden BL, Assad AA (eds) Vehicle routing: methods and studies. Elsevier, Amsterdam, pp 163–197
Li X, Ouyang Y (2010) A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions. Transp Res Part B 44(4):535–548
Lin II, Mahmassani HS (2002) Can online grocers deliver? Some logistics considerations. Trans Res Rec 1817:17–24
Madsen O (1983) Methods for solving combined two level location-routing problems of realistic dimensions. Eur J Oper Res 12:295–301
Maister DH (1976) Centralization of Inventories and the ‘Square Root Law’. Int J Phys Distrib 6(3):124–134
Min H, Jayaraman V, Srivastava R (1998) Combined location-routing problems: a synthesis and future research directions. Eur J Oper Res 108:1–15
Nagy G, Salhi S (1996) Nested heuristic methods for the location-routeing problem. J Oper Res Soc 47(9):1166–1174
Ouyang Y (2007) Design of vehicle routing zones for large-scale distribution systems. Transp Res Part B 41(10):1079–1093
Ouyang Y, Daganzo CF (2006) Discretization and validation of the continuum approximation scheme for terminal system design. Trans Sci 40:89–98
Pulido R (2007) Diseño de un sistema de reparto a domicilio con ventanas de tiempo inmediatas mediante modelación continua. Memoria de titulación, Escuela de Ingeniería, P. Universidad Católica de Chile
Punakivi M, Saranen J (2001) Identifying the success factors in e-grocery home delivery. Int J Retail Distrib Manag 29(4):156–163
Shen ZJ, Lian Q (2006) Incorporating inventory and routing costs in strategic location models. Eur J Oper Res 179:372–389
The Economist (2013) Retail: Mixing bricks with clicks. Printed Edition of March 23rd, 2013
The Economist (2013) Shopping: The emporium strikes back. Printed Edition of July 13th, 2013
The Economist (2014) E-commerce: Same-day dreamer. Printed Edition of May 3rd, 2014
Acknowledgments
The authors wish to thank http://www.Bazuca.com for its participation in this study.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pulido, R., Muñoz, J.C. & Gazmuri, P. A continuous approximation model for locating warehouses and designing physical and timely distribution strategies for home delivery. EURO J Transp Logist 4, 399–419 (2015). https://doi.org/10.1007/s13676-014-0059-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13676-014-0059-z