The Monte Carlo First-Come-First-Served Heuristic for Network Revenue Management

30 Pages Posted: 28 May 2015

See all articles by Nicolas Houy

Nicolas Houy

University of Lyon 2 - Groupe d'Analyse et de Théorie Economique (GATE)

Francois Le Grand

EMLYON Business School

Date Written: May 22, 2015

Abstract

We introduce the Monte-Carlo based heuristic with first-come-first-served approximation for future optimal strategy (MC-FCFS) in order to maximize profit in a network revenue management problem. Like the randomized linear programming (RLP) model, one purpose of the MC-FCFS heuristic is to have information about displacement costs, considering the full probability distribution of future demands instead of a simplified degenerate distribution as in the deterministic linear programming (DLP) model. However, this information is conveyed by applying the FCFS heuristic as a future strategy rather than using the optimal ex-post profits as in the RLP heuristic. We show that MC-FCFS performs approximately as well as the RLP heuristic at a much lower computational cost and much better than the DLP heuristic at maximizing profit in a multi-night hotel booking setting with or without planned upgrades.

Keywords: Network revenue management, Monte-Carlo simulations, randomized linear programming

JEL Classification: C44, C63

Suggested Citation

Houy, Nicolas and Le Grand, François, The Monte Carlo First-Come-First-Served Heuristic for Network Revenue Management (May 22, 2015). Available at SSRN: https://ssrn.com/abstract=2611049 or http://dx.doi.org/10.2139/ssrn.2611049

Nicolas Houy (Contact Author)

University of Lyon 2 - Groupe d'Analyse et de Théorie Economique (GATE) ( email )

93, chemin des Mouilles
Ecully, 69130
France

François Le Grand

EMLYON Business School ( email )

23 Avenue Guy de Collongue
Ecully, 69132
France

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