Dynamic Demand Management for Parcel Lockers

References

• Akkerman F, Dieter P, Mes M (2025) Learning dynamic selection and pricing of out-of-home deliveries. Transportation Sci. 59(2):250–278.Link, Google Scholar
• Amazon (2023) How to use Amazon Locker, the free and convenient way to pick up packages securely outside of your home. Retrieved September 3, 2024, https://www.aboutamazon.com/news/operations/how-to-use-amazon-locker.Google Scholar
• Baek J, Ma W (2022) Technical note—Bifurcating constraints to improve approximation ratios for network revenue management with reusable resources. Oper. Res. 70(4):2226–2236.Link, Google Scholar
• Bergstra J, Yamins D, Cox D (2013) Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. Dasgupta S, McAllester D, eds. Proc. 30th Internat. Conf. Machine Learn., vol. 28 (PMLR, New York), 115–123.Google Scholar
• Bergstra J, Bardenet R, Bengio Y, Kégl B (2011) Algorithms for hyper-parameter optimization. Shawe-Taylor J, Zemel R, Bartlett P, Pereira F, Weinberger K, eds. Advances in Neural Information Processing Systems, vol. 24 (Curran Associates, Red Hook, NY).Google Scholar
• Boysen N, Fedtke S, Schwerdfeger S (2021) Last-mile delivery concepts: A survey from an operational research perspective. OR Spectrum 43:1–58.Crossref, Google Scholar
• DHL (2022) DHL online shopper report 2022. Retrieved September 3, 2024, https://www.dhl.com/content/dam/dhl/local/global/dhl-parcel/documents/pdf/g0-parcelconnect-dhl-online-shopper-report-2022-ebook.pdf.Google Scholar
• DHL (2024) 2024 e-commerce trends report. Retrieved February 19, 2026, https://www.dhl.com/content/dam/dhl/local/global/dhl-ecommerce/documents/pdf/g0-dhl-e-commerce-trends-report-2024.pdf.Google Scholar
• Dumez D, Lehuédé F, Péton O (2021) A large neighborhood search approach to the vehicle routing problem with delivery options. Transportation Res. Part B: Methodological 144:103–132.Crossref, Google Scholar
• Fleckenstein D, Klein R, Steinhardt C (2023) Recent advances in integrating demand management and vehicle routing: A methodological review. Eur. J. Oper. Res. 306(2):499–518.Crossref, Google Scholar
• Fleckenstein D, Klein R, Klein V, Steinhardt C (2025) Explaining the performance impact of opportunity costs approximation in integrated demand management and vehicle routing. EURO J. Transp. Logist. 14:100166.Google Scholar
• Galiullina A, Mutlu N, Kinable J, Van Woensel T (2024) Demand steering in a last-mile delivery problem with home and pickup point delivery options. Transportation Sci. 58(2):454–473.Link, Google Scholar
• Gallego G, Stefanescu C (2009) Upgrades, upsells and pricing in revenue management. Working paper, Columbia University, New York.Google Scholar
• Gallego G, Topaloglu H (2019) Revenue Management and Pricing Analytics (Springer, New York).Crossref, Google Scholar
• Gong XY, Goyal V, Iyengar GN, Simchi-Levi D, Udwani R, Wang S (2022) Online assortment optimization with reusable resources. Management Sci. 68(7):4772–4785.Link, Google Scholar
• Gönsch J (2020) How much to tell your customer?: A survey of three perspectives on selling strategies with incompletely specified products. Eur. J. Oper. Res. 280(3):793–817.Crossref, Google Scholar
• Gönsch J, Steinhardt C (2015) On the incorporation of upgrades into airline network revenue management. Rev. Managerial Sci. 9:635–660.Crossref, Google Scholar
• Hovi IB, Pinchasik DR, Dong B, Strømstad H, Brunstad ØL (2023) Parcel lockers as delivery solution: Usage patterns, experiences and effects of network expansions. TØI Report No. 1959/2023, Institute of Transport Economics, Norwegian Centre for Transportation Research, Oslo, Norway.Google Scholar
• Janinhoff L, Klein R, Scholz D (2023) Multitrip vehicle routing with delivery options: A data-driven application to the parcel industry. OR Spectrum 46:241–294.Crossref, Google Scholar
• Janinhoff L, Klein R, Sailer D, Schoppa JM (2024) Out-of-home delivery in last-mile logistics: A review. Comput. Oper. Res 168:106686.Crossref, 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
• Kötschau R, Soeffker N, Ehmke JF (2023) Mobile parcel lockers with individual customer service. Networks 82(4):506–526.Crossref, Google Scholar
• Kutner MH, Nachtsheim CJ, Neter J, Li W (2004) Applied Linear Statistical Models, 5th ed. (McGraw Hill/Irwin, New York).Google Scholar
• Lin LJ (1993) Reinforcement learning for robots using neural networks. PhD dissertation, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
• Ma B, Wong YD, Teo CC (2022) Parcel self-collection for urban last-mile deliveries: A review and research agenda with a dual operations-consumer perspective. Transportation Res. Interdisciplinary Perspect. 16:100719.Crossref, Google Scholar
• Mahadevan S (1996) Average reward reinforcement learning: Foundations, algorithms, and empirical results. Machine Learn. 22:159–195.Crossref, Google Scholar
• Mancini S, Gansterer M, Triki C (2023) Locker box location planning under uncertainty in demand and capacity availability. Omega (Westport) 120:102910.Crossref, Google Scholar
• Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves A, et al. (2015) Human-level control through deep reinforcement learning. Nature 518:529–533.Crossref, Google Scholar
• Owen Z, Simchi-Levi D (2018) Price and assortment optimization for reusable resources. Working paper, Massachusetts Institute of Technology, Cambridge.Google Scholar
• Papier F, Thonemann UW (2010) Capacity rationing in stochastic rental systems with advance demand information. Oper. Res. 58(2):274–288.Link, Google Scholar
• Powell WB (2022) Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions (John Wiley & Sons, Hoboken, NJ).Crossref, Google Scholar
• Püschel T, Schryen G, Hristova D, Neumann D (2015) Revenue management for cloud computing providers: Decision models for service admission control under non-probabilistic uncertainty. Eur. J. Oper. Res. 244(2):637–647.Crossref, Google Scholar
• Puterman ML (1994) Markov Decision Processes: Discrete Stochastic Dynamic Programming (John Wiley & Sons, Hoboken, NJ).Crossref, Google Scholar
• Retail Economics, InPost (2025) Research report: Beyond the doorstep. Retrieved February 19, 2026, https://inpost.co.uk/resources/retail-economics-report-2025.Google Scholar
• Rusmevichientong P, Sumida M, Topaloglu H (2020) Dynamic assortment optimization for reusable products with random usage durations. Management Sci. 66(7):2820–2844.Link, 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
• Sethuraman S, Bansal A, Mardan S, Resende MG, Jacobs TL (2024) Amazon locker capacity management. INFORMS J. Appl. Anal. 54(6):455–470.Link, Google Scholar
• Statista (2022) Chinese favor self-service stations for parcel pick-up. Retrieved September 3, 2024, https://www.statista.com/chart/26656/.Google Scholar
• Strauss AK, Klein R, Steinhardt C (2018) A review of choice-based revenue management: Theory and methods. Eur. J. Oper. Res. 271(2):375–387.Crossref, Google Scholar
• Sutton RS, Barto AG (2018) Reinforcement Learning: An Introduction, 2nd ed. (MIT Press, Cambridge, MA).Google Scholar
• Talluri KT, Van Ryzin GJ (2004) The Theory and Practice of Revenue Management (Springer, New York).Crossref, Google Scholar
• Ulmer MW, Streng S (2019) Same-day delivery with pickup stations and autonomous vehicles. Comput. Oper. Res. 108:1–19.Crossref, Google Scholar
• Ulmer MW, Mattfeld DC, Köster F (2018) Budgeting time for dynamic vehicle routing with stochastic customer requests. Transportation Sci. 52(1):20–37.Link, Google Scholar
• Venipak (2023) Venipak invests €0.5 million in expanding the parcel locker network. Retrieved September 3, 2024, https://venipak.com/lt/en/news/2023-05-15/venipak-invests-e0-5-million-in-expanding-the-parcel-locker-network/.Google Scholar
• Waβmuth K, Köhler C, Agatz N, Fleischmann M (2023) Demand management for attended home delivery—A literature review. Eur. J. Oper. Res. 311(3):801–815.Crossref, Google Scholar
• Zhang S, Sutton RS (2017) A deeper look at experience replay. Working paper, University of Alberta, Alberta.Google Scholar
• Zhu W, Topaloglu H (2024) Performance guarantees for network revenue management with flexible products. Manufacturing Service Oper. Management 26(1):252–270.Link, Google Scholar