Convexity and feedback in approximate dynamic programming for delivery time slot pricing
We consider the revenue management problem of finding profit-maximising prices for delivery time slots in the context of attended home delivery. This multi-stage optimal control problem admits a dynamic programming formulation that is intractable for realistic problem sizes due to the socalled “curs...
| Asıl Yazarlar: | , , |
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| Materyal Türü: | Journal article |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
IEEE
2021
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| _version_ | 1826307533537542144 |
|---|---|
| author | Lebedev, D Margellos, K Goulart, P |
| author_facet | Lebedev, D Margellos, K Goulart, P |
| author_sort | Lebedev, D |
| collection | OXFORD |
| description | We consider the revenue management problem of
finding profit-maximising prices for delivery time slots in the
context of attended home delivery. This multi-stage optimal
control problem admits a dynamic programming formulation
that is intractable for realistic problem sizes due to the socalled “curse of dimensionality”. Therefore, we study three
approximate dynamic programming algorithms both from a
control-theoretical perspective and numerically. Our analysis is
based on real-world data, from which we generate multiple
scenarios to stress-test the robustness of the pricing policies to
errors in model parameter estimates. Our theoretical analysis and
numerical benchmark tests indicate that one of these algorithms,
namely gradient-bounded dynamic programming, dominates the
others with respect to computation time and profit-generation
capabilities of the pricing policies that it generates. |
| first_indexed | 2024-03-07T07:06:02Z |
| format | Journal article |
| id | oxford-uuid:4655b59c-142f-4b8f-966c-7a1a7dc2653c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:06:02Z |
| publishDate | 2021 |
| publisher | IEEE |
| record_format | dspace |
| spelling | oxford-uuid:4655b59c-142f-4b8f-966c-7a1a7dc2653c2022-05-04T08:20:00ZConvexity and feedback in approximate dynamic programming for delivery time slot pricingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4655b59c-142f-4b8f-966c-7a1a7dc2653cEnglishSymplectic ElementsIEEE2021Lebedev, DMargellos, KGoulart, PWe consider the revenue management problem of finding profit-maximising prices for delivery time slots in the context of attended home delivery. This multi-stage optimal control problem admits a dynamic programming formulation that is intractable for realistic problem sizes due to the socalled “curse of dimensionality”. Therefore, we study three approximate dynamic programming algorithms both from a control-theoretical perspective and numerically. Our analysis is based on real-world data, from which we generate multiple scenarios to stress-test the robustness of the pricing policies to errors in model parameter estimates. Our theoretical analysis and numerical benchmark tests indicate that one of these algorithms, namely gradient-bounded dynamic programming, dominates the others with respect to computation time and profit-generation capabilities of the pricing policies that it generates. |
| spellingShingle | Lebedev, D Margellos, K Goulart, P Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title | Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title_full | Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title_fullStr | Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title_full_unstemmed | Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title_short | Convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| title_sort | convexity and feedback in approximate dynamic programming for delivery time slot pricing |
| work_keys_str_mv | AT lebedevd convexityandfeedbackinapproximatedynamicprogrammingfordeliverytimeslotpricing AT margellosk convexityandfeedbackinapproximatedynamicprogrammingfordeliverytimeslotpricing AT goulartp convexityandfeedbackinapproximatedynamicprogrammingfordeliverytimeslotpricing |