UPS Optimizes Delivery Routes

Published Online:https://doi.org/10.1287/inte.2016.0875

References

  • Ausubel JH, Curry AS, Wernick IK (2015) Reconsidering resources—Material, labor, information, and capital in the future security environment. Report, Office of Net Assessment, U.S. Department of Defense, Washington, DC.Google Scholar
  • Campbell AM, Thomas BW (2008) Probabilistic traveling salesman problem with deadlines. Transportation Sci. 42(1):1–21.LinkGoogle Scholar
  • Dash S, Günlük O, Lodi A, Tramontani A (2012) A time bucket formulation for the traveling salesman problem with time windows. INFORMS J. Comput. 24(1):132–147.LinkGoogle Scholar
  • Davenport T (2013) Analytics 3.0. Harvard Bus. Rev., https://hbr.org/2013/12/analytics-30.Google Scholar
  • El-Sherbeny N (2010) Vehicle routing with time windows: An overview of exact, heuristic and metaheuristic methods. J. King Saud Univ. Sci. 22(3):123–131.CrossrefGoogle Scholar
  • Groër C, Golden B, Wasil E (2009) The consistent vehicle routing problem. Manufacturing Service Oper. Management. 11(4): 630–643.LinkGoogle Scholar
  • Kovacs AA, Golden BL, Hartl RF, Parragh SN (2014) Vehicle routing problems in which consistency considerations are important: A survey. Networks 64(3):192–213.CrossrefGoogle Scholar
  • Hurley S, Snyder S, Trevillian R, Fry T (2014) Enhanced location information for points of interest. US Patent 9,725,400, filed September 9, 2010, issued May 13 2014.Google Scholar
  • Ingber L (1993) Simulated annealing: Practice versus theory. Math. Comput. Model. 18(11):29–57.CrossrefGoogle Scholar
  • Lemaréchal C (2001) Lagrangian relaxation. Jünger M, Naddef D, eds. Computational Combinatorial Optimization: Optimal or Provably Near-Optimal Solutions [Based on a Spring School] (Springer-Verlag, London), 112–156.CrossrefGoogle Scholar
  • Levis J (2016) Jack Levis: The hardest step in innovation? Looking foolish in front of the crowd (again and again … and again). Accessed June 9, 2016, https://www.ted.com/watch/ted-institute/ted-ups/jack-levis-the-hardest-step-in-innovation.Google Scholar
  • Levis J, Mohr D, Nuggehalli R, D’Antona A, Hu P (2009) Systems and methods for dynamically updating a dispatch plan. US Patent 7,624,024 B2, filed April 18, 2005, issued November 24, 2009.Google Scholar
  • Lin S, Kernighan BW (1973) An effective heuristic algorithm for the traveling-salesman problem. Oper. Res. 21(2):498–516.LinkGoogle Scholar
  • Ropke S, Pisinger D (2006) An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Sci. 40(4):455–472.LinkGoogle Scholar
  • Sungur I, Ren Y, Ordóñez F, Dessouky M, Zhong H (2010) A model and algorithm for courier delivery problem with uncertainty. Transportation Sci. 44(2):193–205.LinkGoogle Scholar
  • Zhong H (2010) Core area territory planning for optimizing driver familiarity and route flexibility. US Patent 7,840,319 B2, filed December 8, 2009, issued November 10, 2010.Google Scholar
  • Zhong H, Zaret D (2008a) Core area territory planning for optimizing driver familiarity and route flexibility. US Patent 7,363,126 B1, filed August 22, 2003, issued April 22, 2008.Google Scholar
  • Zhong H, Zaret D (2008b) Core area territory planning for optimizing driver familiarity and route flexibility. US Patent 7,660,651 A1, filed December 21, 2007, issued June 19, 2008.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.