Hotel Capacity Planning Using Queuing Systems and Meta-Heuristic Algorithms

Abstract

Deciding on optimal hotel capacity is strategically important and even very sensitive for investors in the hospitality industry. This article is an attempt to determine optimal hotel capacity with a novel approach, and then present a mathematical optimization model based on queuing theory. In that respect, upon simulating the hotel check-in system via the models of queuing and making use a limited two-dimensional backpack pattern, the optimal capacity and the hotel rooms number are acquired. Given the fact that the suggested model has high complexity in large scales, a meta-innovative approach is utilized to solve the problem of optimal hotel capacity determination. Contrary to previous models and approaches, merely applied to a specific hypothetical situation, the queuing theory, thanks to the existence of various models and the power to generate new patterns utilizing Markov chains, makes it possible to adapt the proposed model to different real conditions. There exist several queuing models, which can be implemented based on different conditions. Such models are progressively increasing and being expanded according to various requirements for modeling real environments. It seems necessary and innovative to expand the model proposed in the present study, employing non-Markov queuing models along with the general distribution functions.

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