Simulation-based meta-heuristic approach for booking limits problem at a hotel baby

In this work, a meta-heuristic approach integrated the genetic algorithm (GA) with ranking and selection (R&S) is proposed to solve for a good enough solution of the hard stochastic simulation optimization problem (SSOP) with huge solution space. First, a rough model is used as a fitness evaluat...

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Veröffentlicht in:2012 International Conference on Information Security and Intelligence Control (ISIC) S. 152 - 155
Hauptverfasser: Shih-Cheng Horng, Feng-Yi Yang
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2012
Schlagworte:
baby hotel revenue management
Biological cells
booking limits
Computational modeling
genetic algorithm
Genetic algorithms
Optimization
Pediatrics
ranking and selection
simulation optimization
Stochastic processes
Vectors
ISBN:9781467325875, 1467325872
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In this work, a meta-heuristic approach integrated the genetic algorithm (GA) with ranking and selection (R&S) is proposed to solve for a good enough solution of the hard stochastic simulation optimization problem (SSOP) with huge solution space. First, a rough model is used as a fitness evaluation in the GA to select N roughly good solutions from entire solution space. Then, we proceed with the R&S policy to search for a good enough solution from the N roughly good solutions. Finally, the meta-heuristic approach is applied to a booking limits problem at a hotel baby, which is formulated as a hard SSOP that consists of a huge solution space comprised by the vector of booking limits. The vector of good enough booking limits obtained by the proposed approach is promising in the aspects of solution quality and computational efficiency.
ISBN:9781467325875
1467325872
DOI:10.1109/ISIC.2012.6449729