Monday, 15:15 - 15:40 h, Room: MA 144

 

Retsef Levi
Near-optimal algorithms for assortment planning under dynamic substitution and stochastic demand

Coauthors: Vineet Goyal, Danny Segev

 

Abstract:
We consider a single-period assortment planning problem under a dynamic-substitution model with stochastic demand and give a polynomial time approximation scheme for the problem under fairly general assumptions. Our algorithm computes an assortment containing only a small number of product types and obtains near-optimal revenue. We also present several complexity results for the problem that indicate that our assumptions are almost 'necessary' to solve it efficiently.

 

Talk 1 of the invited session Mon.3.MA 144
"Approximation algorithms for stochastic revenue management optimization" [...]
Cluster 22
"Stochastic optimization" [...]

 

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