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C++ library of Revenue Management and Optimisation classes and functions
RMOL::MCOptimiser Class Reference

#include <rmol/bom/MCOptimiser.hpp>

List of all members.

Static Public Member Functions

static void optimalOptimisationByMCIntegration (stdair::LegCabin &)
static
stdair::GeneratedDemandVector_T 
generateDemandVector (const stdair::MeanValue_T &, const stdair::StdDevValue_T &, const unsigned int &)
static void optimisationByMCIntegration (stdair::LegCabin &)

Detailed Description

Utility methods for the Monte-Carlo algorithms.


Member Function Documentation

void RMOL::MCOptimiser::optimalOptimisationByMCIntegration ( stdair::LegCabin &  ioLegCabin) [static]

Calculate the optimal protections for the set of buckets/classes given in input, and update those buckets accordingly.
The Monte Carlo Integration algorithm (see The Theory and Practice of Revenue Management, by Kalyan T. Talluri and Garret J. van Ryzin, Kluwer Academic Publishers, for the details) is used.

Definition at line 28 of file MCOptimiser.cpp.

stdair::GeneratedDemandVector_T RMOL::MCOptimiser::generateDemandVector ( const stdair::MeanValue_T &  iMean,
const stdair::StdDevValue_T &  iStdDev,
const unsigned int &  K 
) [static]

Monte-Carlo

Definition at line 154 of file MCOptimiser.cpp.

Referenced by optimisationByMCIntegration().

void RMOL::MCOptimiser::optimisationByMCIntegration ( stdair::LegCabin &  ioLegCabin) [static]

Definition at line 175 of file MCOptimiser.cpp.

References generateDemandVector().

Referenced by RMOL::Optimiser::optimiseUsingOnDForecast().


The documentation for this class was generated from the following files: