Integrating commercial and residential pickup and delivery networks: A case study

This paper presents a strategic analysis of the network design problem faced by pickup and delivery companies operating in metropolitan areas and serving two or more classes of customers. The focus is on a division that treats commercial and residential customers separately, a situation motivated by their respective geographic densities and the size and frequency of their demand. In constructing driver work areas, it is necessary to take into account expected demand, vehicle capacity, time on the road, and the aspect ratio of the individual territories. This leads to a capacitated clustering problem with side constraints that has been the subject of intense research over the last decade.

[1]  G. Nemhauser,et al.  An Optimization Based Heuristic for Political Districting , 1998 .

[2]  Luiz Antonio Nogueira Lorena,et al.  A column generation approach to capacitated p-median problems , 2004, Comput. Oper. Res..

[3]  G. Nemhauser,et al.  Integer Programming , 2020 .

[4]  Jonathan F. Bard,et al.  Large-scale pickup and delivery work area design , 2012, Comput. Oper. Res..

[5]  Elena Fernández,et al.  A reactive GRASP for a commercial territory design problem with multiple balancing requirements , 2009, Comput. Oper. Res..

[6]  Mark S. Daskin,et al.  Network and Discrete Location: Models, Algorithms and Applications , 1995 .

[7]  Khaled S. Al-Sultan,et al.  Computational experience on four algorithms for the hard clustering problem , 1996, Pattern Recognit. Lett..

[8]  Gilbert Laporte,et al.  AN ALGORITHM FOR THE DESIGN OF MAILBOX COLLECTION ROUTES IN URBAN AREAS , 1989 .

[9]  Jonathan F. Bard,et al.  Pickup and delivery network segmentation using contiguous geographic clustering , 2011, J. Oper. Res. Soc..

[10]  Marshall L. Fisher,et al.  A Periodic Inventory Routing Problem at a Supermarket Chain , 2004, Oper. Res..

[11]  Carlos F. Daganzo,et al.  On Planning and Design of Logistics Systems for Uncertain Environments , 1999 .

[12]  Michael A. Trick,et al.  Cliques and clustering: A combinatorial approach , 1998, Oper. Res. Lett..

[13]  Paolo Toth,et al.  VRP with Backhauls , 2002, The Vehicle Routing Problem.

[14]  François Vanderbeck,et al.  On Dantzig-Wolfe Decomposition in Integer Programming and ways to Perform Branching in a Branch-and-Price Algorithm , 2000, Oper. Res..

[15]  Jonathan F. Bard,et al.  Validating vehicle routing zone construction using Monte Carlo simulation , 2010, Eur. J. Oper. Res..

[16]  J. Yang,et al.  An optimization approach to partitional data clustering , 2009, J. Oper. Res. Soc..

[17]  Andreas Drexl,et al.  Fast Approximation Methods for Sales Force Deployment , 1999 .

[18]  J. Mulvey,et al.  Solving capacitated clustering problems , 1984 .

[19]  André Langevin,et al.  Design of multiple-vehicle delivery tours satisfying time constraints , 1989 .

[20]  H. Young.  Measuring the Compactness of Legislative Districts , 1988 .

[21]  Yanfeng Ouyang,et al.  Design of vehicle routing zones for large-scale distribution systems , 2007 .

[22]  Marcos Negreiros,et al.  The capacitated centred clustering problem , 2006, Comput. Oper. Res..

[23]  Jonathan F. Bard,et al.  Large-scale constrained clustering for rationalizing pickup and delivery operations , 2009 .