Crowdkeeping in Last-Mile Delivery

References

• Agatz N, Campbell A, Fleischmann M, Savelsbergh M (2011) Time slot management in attended home delivery. Transportation Sci. 45(3):435–449.Link, Google Scholar
• Alnaggar A, Gzara F, Bookbinder JH (2021) Crowdsourced delivery: A review of platforms and academic literature. Omega 98:102139.Crossref, Google Scholar
• Applegate DL, Bixby RE, Chvátal V, Cook WJ (2007) The Traveling Salesman Problem: A Computational Study (Princeton University Press, Princeton, NJ).Google Scholar
• Archetti C, Guerriero F, Macrina G (2021) The online vehicle routing problem with occasional drivers. Comput. Oper. Res. 127:105144.Crossref, Google Scholar
• Arslan O (2021) The location-or-routing problem. Transportation Res. Part B: Methodological 147:1–21.Crossref, Google Scholar
• Arslan AM, Agatz N, Kroon L, Zuidwijk R (2019) Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers. Transportation Sci. 53(1):222–235.Link, Google Scholar
• Beardwood J, Halton JH, Hammersley JM (1959) The shortest path through many points. Math. Proc. Cambridge Philos. Soc. 55(4):299–327.Crossref, Google Scholar
• Bruck BP, Cordeau JF, Iori M (2018) A practical time slot management and routing problem for attended home services. Omega 81:208–219.Crossref, Google Scholar
• Bruck BP, Castegini F, Cordeau JF, Iori M, Poncemi T, Vezzali D (2020) A decision support system for attended home services. INFORMS J. Appl. Anal. 50(2):137–152.Link, Google Scholar
• CaiNiao (2023) How to make money by being a keeper. [In Chinese.] Accessed January 1, 2023 https://cn.alicdn.com/video/cainiao/yizhan/main.mp4.Google Scholar
• Campbell AM, Savelsbergh M (2006) Incentive schemes for attended home delivery services. Transportation Sci. 40(3):327–341.Link, Google Scholar
• Carbone V, Rouquet A, Roussat C (2017) The rise of crowd logistics: A new way to co-create logistics value. J. Bus. Logist. 38(4):238–252.Crossref, Google Scholar
• Cavdar B, Sokol J (2015) A distribution-free TSP tour length estimation model for random graphs. Eur. J. Oper. Res. 243(2):588–598.Crossref, Google Scholar
• Dantzig G, Fulkerson R, Johnson S (1954) Solution of a large-scale traveling-salesman problem. J. Oper. Res. Soc. Amer. 2(4):393–410.Link, Google Scholar
• Dayarian I, Savelsbergh M (2020) Crowdshipping and same-day delivery: Employing in-store customers to deliver online orders. Production Oper. Management 29(9):2153–2174.Crossref, Google Scholar
• Deloison T, Hannon E, Huber A, Heid B, Klink C, Sahay R, Wolff C (2020) The future of the last-mile ecosystem. Technical report, World Economic Forum, Geneva.Google Scholar
• Devari A, Nikolaev AG, He Q (2017) Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers. Transportation Res. Part E: Logist. Transportation Rev. 105:105–122.Crossref, Google Scholar
• Franceschetti A, Jabali O, Laporte G (2017) Continuous approximation models in freight distribution management. TOP 25(3):413–433.Crossref, Google Scholar
• Gendreau M, Laporte G, Semet F (1997) The covering tour problem. Oper. Res. 45(4):568–576.Link, Google Scholar
• Hasija S, Shen ZJM, Teo CP (2020) Smart city operations: Modeling challenges and opportunities. Manufacturing Service Oper. Management 22(1):203–213.Link, Google Scholar
• Jacobs K, Warner S, Rietra M, Mazza L, Buvat J, Khadikar A, Cherian S, Khemka Y (2019) The last-mile delivery challenge. Technical report, Capgemini Research Institute, Paris.Google Scholar
• Joerss M, Schröder J, Neuhaus F, Klink C, Mann F (2016) Parcel delivery: The future of last mile. Technical report, McKinsey & Company, Chicago.Google Scholar
• Jozefowiez N (2014) A branch-and-price algorithm for the multivehicle covering tour problem. Networks 64(3):160–168.Crossref, Google Scholar
• Kartal Z, Hasgul S, Ernst AT (2017) Single allocation p-hub median location and routing problem with simultaneous pick-up and delivery. Transportation Res. Part E: Logist. Transportation Rev. 108:141–159.Crossref, Google Scholar
• Klein R, Mackert J, Neugebauer M, Steinhardt C (2018) A model-based approximation of opportunity cost for dynamic pricing in attended home delivery. OR Spectrum 40(4):969–996.Crossref, Google Scholar
• Klein R, Neugebauer M, Ratkovitch D, Steinhardt C (2019) Differentiated time slot pricing under routing considerations in attended home delivery. Transportation Sci. 53(1):236–255.Link, Google Scholar
• Koch S, Klein R (2020) Route-based approximate dynamic programming for dynamic pricing in attended home delivery. Eur. J. Oper. Res. 287(2):633–652.Crossref, Google Scholar
• Le TV, Stathopoulos A, Van Woensel T, Ukkusuri SV (2019) Supply, demand, operations, and management of crowdshipping services: A review and empirical evidence. Transportation Res. Part C: Emerging Tech. 103:83–103.Crossref, Google Scholar
• Lin YH, Wang Y, He D, Lee LH (2020) Last-mile delivery: Optimal locker location under multinomial logit choice model. Transportation Res. Part E: Logist. Transportation Rev. 142:102059.Crossref, Google Scholar
• Martinez-Sykora A, McLeod F, Lamas-Fernandez C, Bektaş T, Cherrett T, Allen J (2020) Optimised solutions to the last-mile delivery problem in London using a combination of walking and driving. Ann. Oper. Res. 295(2):645–693.Crossref, Google Scholar
• McKinnon AC, Tallam D (2003) Unattended delivery to the home: An assessment of the security implications. Internat. J. Retail Distribution Management 31(1):30–41.Crossref, Google Scholar
• Merchan D, Pachon J, Arora J, Konduri K, Winkenbach M, Parks S, Noszek J (2021) Amazon last mile routing research challenge data set. Accessed January 6, 2022, https://registry.opendata.aws/amazon-last-mile-challenges.Google Scholar
• Perboli G, Tadei R, Vigo D (2011) The two-echelon capacitated vehicle routing problem: Models and math-based heuristics. Transportation Sci. 45(3):364–380.Link, Google Scholar
• Pickme (2024) Let’s build tomorrow’s delivery together! [In French.] Accessed February 11, 2024, https://www.mypickme.com/.Google Scholar
• Qi W, Li L, Liu S, Shen ZJM (2018) Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact. Manufacturing Service Oper. Management 20(4):737–751.Link, Google Scholar
• Rohmer S, Gendron B (2020) A guide to parcel lockers in last mile distribution: Highlighting challenges and opportunities from an or perspective. Technical report, CIRRELT, Montreal.Google Scholar
• Savelsbergh M, Van Woensel T (2016) 50th anniversary invited article—City logistics: Challenges and opportunities. Transportation Sci. 50(2):579–590.Link, Google Scholar
• Schwerdfeger S, Boysen N (2020) Optimizing the changing locations of mobile parcel lockers in last-mile distribution. Eur. J. Oper. Res. 285(3):1077–1094.Crossref, Google Scholar
• Spliet R, Gabor AF (2015) The time window assignment vehicle routing problem. Transportation Sci. 49(4):721–731.Link, Google Scholar
• Toth P, Vigo D (2014) Vehicle Routing: Problems, Methods, and Applications (Society for Industrial and Applied Mathematics, Philadelphia).Crossref, Google Scholar
• Ulmer MW (2020) Dynamic pricing and routing for same-day delivery. Transportation Sci. 54(4):1016–1033.Link, Google Scholar
• Ulmer MW, Savelsbergh M (2020) Workforce scheduling in the era of crowdsourced delivery. Transportation Sci. 54(4):1113–1133.Link, Google Scholar
• Vidal T, Laporte G, Matl P (2020) A concise guide to existing and emerging problem variants. Eur. J. Oper. Res. 286(2):401–416.Crossref, Google Scholar
• Yang X, Strauss AK (2017) An approximate dynamic programming approach to attended home delivery management. Eur. J. Oper. Res. 263(3):935–945.Crossref, Google Scholar
• Yildiz B, Savelsbergh M (2020) Pricing for delivery time flexibility. Transportation Res. Part B: Methodological 133:230–256.Crossref, Google Scholar