The Monte Carlo first-come-first-served heuristic for network revenue management

Nicolas Houy and François Le Grand
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François Le Grand: EM - EMLyon Business School

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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 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-cmp and nep-ore
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