TY  - JOUR
A1  - Schlosser, Rainer
T1  - Scalable relaxation techniques to solve stochastic dynamic multi-product pricing problems with substitution effects
JF  - Journal of revenue and pricing management
N2  - In many businesses, firms are selling different types of products, which share mutual substitution effects in demand. To compute effective pricing strategies is challenging as the sales probabilities of each of a firm's products can also be affected by the prices of potential substitutes. In this paper, we analyze stochastic dynamic multi-product pricing models for the sale of perishable goods. To circumvent the limitations of time-consuming optimal solutions for highly complex models, we propose different relaxation techniques, which allow to reduce the size of critical model components, such as the state space, the action space, or the set of potential sales events. Our heuristics are able to decrease the size of those components by forming corresponding clusters and using subsets of representative elements. Using numerical examples, we verify that our heuristics make it possible to dramatically reduce the computation time while still obtaining close-to-optimal expected profits. Further, we show that our heuristics are (i) flexible, (ii) scalable, and (iii) can be arbitrarily combined in a mutually supportive way.
KW  - multi-product pricing
KW  - substitution effects
KW  - data-driven demand
KW  - dynamic
KW  - programming
KW  - heuristics
Y1  - 2020
U6  - https://doi.org/10.1057/s41272-020-00249-z
SN  - 1476-6930
SN  - 1477-657X
VL  - 20
IS  - 1
SP  - 54
EP  - 65
PB  - Palgrave Macmillan
CY  - Basingstoke
ER  -