(Single Resource) dynamic program: satisfies the printed recursion and boundary conditions
ProvedMarkovChainChoice.SingleResource.value_bellmanchoice-modelsdynamic-programmingp2o-batch-p200bp2o-gran-per-chapterp2o-plan-paperp2o-v1revenue-management
Let be a Markov chain choice model, revenues and the number of periods. The value functions of the (Single Resource) dynamic program satisfy the boundary conditions for all and for , and for and ,
This is the first line of the (Single Resource) display: with probability a customer buys product , earning and leaving units, and otherwise capacity carries over to period . It confirms that the rearranged recursion used to define is the dynamic program as printed.
Formalization Note is value M r T t x, defined through the rearranged second line of the display; this theorem states that it satisfies the first line. The maximum is Finset.sup' over all subsets of .
Preamble
import Mathlib import Definitions.Def_MarkovChainChoice_SingleResource_ValueFunction open MarkovChainChoice.Shared
Formal statement
namespace MarkovChainChoice.SingleResource
theorem value_bellman {n : ℕ} (M : Model n) (r : Fin n → ℝ) (T : ℕ) :
(∀ x, value M r T (T + 1) x = 0) ∧
(∀ t, 1 ≤ t → t ≤ T → value M r T t 0 = 0) ∧
∀ t x, 1 ≤ t → t ≤ T → 1 ≤ x →
value M r T t x =
(Finset.univ : Finset (Finset (Fin n))).sup' Finset.univ_nonempty (fun S =>
∑ j, purchase M S j * (r j + value M r T (t + 1) (x - 1)) +
(1 - ∑ j, purchase M S j) * value M r T (t + 1) x) := by sorry
end MarkovChainChoice.SingleResource
Source
Feldman, Topaloglu, Revenue Management Under the Markov Chain Choice Model, Oper. Res. 65(5), 2017, pp. 1328–1329, Section 5, (Single Resource) and its boundary conditions
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.