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Last-100-Meter Vertical Delivery
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Problem Definition: On-demand delivery platforms increasingly distinguish themselves through faster and more reliable order fulfillment, yet the final delivery stage inside high-rise buildings can remain time-consuming and uncertain. We identify this overlooked stage as the last-100-meter vertical delivery problem and formalize it as the Elevator Delivery Problem with Deadlines (EDPD) under uncertain elevator waiting times. Elevator waiting-time data from Beijing office buildings show substantial dispersion, pronounced right tails, and systematic heterogeneity across call floors, requested travel directions, and elevator loading states. Methodology/results: To capture these empirical patterns, we use a directed network to distinguish elevator calls by call floor and requested travel direction and a scenario-wise ambiguity set to characterize each loading state with conditional moment and support information. To quantify delay risk, we propose the Flexible Essential Riskiness Index (FERI), which extends the Essential Riskiness Index (ERI) by allowing the ERI feasibility condition to be relaxed with a penalty. FERI jointly accounts for the probability and magnitude of lateness while remaining finite and informative in delay-prone instances, where ERI is inapplicable. Integrating these elements, we propose a last-100-meter vertical delivery model, derive an equivalent mixed-integer second-order cone reformulation, develop a Benders decomposition algorithm to solve the model exactly, and design a hybrid heuristic that combines a residual-capacity-based Label strategy with the Deadline and Floor strategies for real-time sequencing decisions. Managerial implications: Simulation experiments show that the Benders decomposition substantially improves tractability and that our proposed model provides more reliable out-of-sample performance than sample-average approximation under distributional misspecification. A case study using real elevator data from Weiya Building shows that the exact solution approach and the Label strategy outperform practical Floor and Deadline strategies. The results also show that reliable delivery sequences may accept additional but more predictable in-elevator riding time to avoid long and volatile waits. Mechanisms for platform--building coordination, including anticipatory elevator calling and dedicated elevator access, can further reduce vertical delivery delay risk. More broadly, this work highlights the role of vertical logistics in enabling reliable urban on-demand fulfillment.
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Title: Last-100-Meter Vertical Delivery
Description:
<div>
Problem Definition: On-demand delivery platforms increasingly distinguish themselves through faster and more reliable order fulfillment, yet the final delivery stage inside high-rise buildings can remain time-consuming and uncertain.
We identify this overlooked stage as the last-100-meter vertical delivery problem and formalize it as the Elevator Delivery Problem with Deadlines (EDPD) under uncertain elevator waiting times.
Elevator waiting-time data from Beijing office buildings show substantial dispersion, pronounced right tails, and systematic heterogeneity across call floors, requested travel directions, and elevator loading states.
Methodology/results: To capture these empirical patterns, we use a directed network to distinguish elevator calls by call floor and requested travel direction and a scenario-wise ambiguity set to characterize each loading state with conditional moment and support information.
To quantify delay risk, we propose the Flexible Essential Riskiness Index (FERI), which extends the Essential Riskiness Index (ERI) by allowing the ERI feasibility condition to be relaxed with a penalty.
FERI jointly accounts for the probability and magnitude of lateness while remaining finite and informative in delay-prone instances, where ERI is inapplicable.
Integrating these elements, we propose a last-100-meter vertical delivery model, derive an equivalent mixed-integer second-order cone reformulation, develop a Benders decomposition algorithm to solve the model exactly, and design a hybrid heuristic that combines a residual-capacity-based Label strategy with the Deadline and Floor strategies for real-time sequencing decisions.
Managerial implications: Simulation experiments show that the Benders decomposition substantially improves tractability and that our proposed model provides more reliable out-of-sample performance than sample-average approximation under distributional misspecification.
A case study using real elevator data from Weiya Building shows that the exact solution approach and the Label strategy outperform practical Floor and Deadline strategies.
The results also show that reliable delivery sequences may accept additional but more predictable in-elevator riding time to avoid long and volatile waits.
Mechanisms for platform--building coordination, including anticipatory elevator calling and dedicated elevator access, can further reduce vertical delivery delay risk.
More broadly, this work highlights the role of vertical logistics in enabling reliable urban on-demand fulfillment.
</div>.
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