Article ID: | iaor20171349 |
Volume: | 16 |
Issue: | 2 |
Start Page Number: | 115 |
End Page Number: | 124 |
Publication Date: | Apr 2017 |
Journal: | J Revenue Pricing Manag |
Authors: | Rottembourg Benot, Masson Jacques |
Keywords: | management, decision, optimization, programming: markov decision |
In the hospitality industry, an allotment is a block of pre‐negociated ‘rooms’ which have been bought by a tour operator. In the context of campsites, allotments represent a significant share of the mobile homes sales. For the campsite owner, dealing with tour operator allotment requests is a poisoned chalice. On one hand these pre‐booked sales are more or less a guarantee of selling a good share of its inventory. On the other hand, the discount level is so high that selling the whole inventory through allotments could potentially ruin the business. Hence, a balance must be found between allotment contracts and estimated direct sales to final customers (at full price, or lightly discounted price). The purpose of the present paper is to show that the stochastic optimisation problem at stake is highly combinatorial and that algorithmic approaches relying on continuous relaxations of the demand (‘bid price’) behave poorly. For multi‐site allotment optimisation with service level requirements from tour operators, we developed a Lagrange decomposition technique based on local Markov Decision Process solvers that outperforms classic "fluid displacement" approaches. We provide experimental results on instances with 200 campsites 20,000 mobile homes and 15 tour operators inspired from a leading European actor of the campsite industry.