The namespaces specified in this document are:

Namespace | Assembly |
---|---|

Net.Kniaz.Math.AHP.Tests | Net.Kniaz.AHP |

Net.Kniaz.Math.AHP | Net.Kniaz.AHP |

Type | Summary |
---|---|

TestAHP | Summary description for TestProrities. |

Summary description for TestProrities.

Name | Access | Summary |
---|---|---|

TestAHP() | public | Initializes a new instance of the class. |

Name | Access | Summary |
---|---|---|

TestChoiceMatrix() : Void | public | |

TestConsistencyRatio() : Void | public | |

TestExpansionUtility() : Void | public | |

TestFeatureSelection() : Void | public | AHP model for the computer system with 3 criteria - scalability, maintanablity, reliability and 19 features f0 to f18. Features have been rated against ech other and feature f12 is most preferable with 19% |

TestPriorities() : Void | public | |

TestVacationSpotSelection() : Void | public | Vacation Hierarchy Model by Saaty et all Criteria: Activities, Nightlife, Siteseeing, Cost Choices: Orlando, San Fran, New York; Inputs are Activities Orlando SF NY Orlando 1 4 3 SF 1 2 NY 1 That is Orlando is more preffered than SF and NY. Also SF is more prefferred than NY |

Type | Summary |
---|---|

AHPModel | This class implements a decision model of the Analytic Hierarchy Process by Saaty. (T.L. Saaty "The Analytic Hierarchy Process", McGraw-Hill New York, 1980) The client of the class must provide decision making criteria that are scored against each other via a pairwise comparison (using the 1-9 scale proposed by Saaty) and the choices tht are scored for every criteria also using binary comparison process. Client should use the AddCriteria method for the criteria and AddCriterionRatedChoices for choices scored agains the criteria. Order in which choices are added to the model must match the ordering of criteria in the matrix. It is assumed that all matrixes submittd to the model are symmetrical, inverse. for example: say we are trying to decide between Orlando, SF and NY as vacation places (see the unit test for a full example). We have 4 criteria to based our selection on: Activities, Nightlife, Siteseeing, Cost We start build our crteria matrix by comparing activities with remaining 3 criteria and using the scale from 1 (equally preferable to 9: extremely more preferable). Then we score nightlife against siteseeing and Cost and finally we compart Siteseeing ang cost. There is no reason to compare Cost to Activities again because it will be just a reverse from the comparison made in the first choice. As a result we get the following matrix: Activities NightLife SiteSeeing Cost Activites 1 3 4 5 Nigthlife 1 0.5 0.33333 SiteSeeing 1 3 Cost 1 The left lower triangle of the matrix should be left to 0 because the class will transpose and take inverse of the upper right corner. After setting up criteria and choices the client should call the calculate model method. final result (choices scored against each criteria) are contained in the model result matrix. Each column of the result matrix represents scored of choices against each criteria This assembly uses the GeneralMatrix package for the matrix algebra. |

Constants | Random Indices values (Consistency Indices for randomly selected values in the priority matrix) taken from Saaty. |

PrioritiesSelector | This class implements the Saaty's method for estimating eigenvalues of the priorities matrix. |

Name | Access | Summary |
---|---|---|

AHPModel() | public | Parametrized Constructor |

Name | Access | Summary |
---|---|---|

CalculatedChoices : GeneralMatrix | public | |

CalculatedCriteria : GeneralMatrix | public | Criteria priorities as calculated by the model. A matrix of n by 1 |

ChoiceMatrix : GeneralMatrix | public | Model choices scored in pairwise comparison for each criteria A matrix of n by n*m |

ConsistencyRatio : GeneralMatrix | public | Matrix of consistency ratios for the model size of n+1 where n is number of criteria First row represents consistency ratio for the |

ModelResult : GeneralMatrix | public | Result |

RatedCriteria : GeneralMatrix | public | Raw criteria scored after the pairwise comparison A matrix of n by n |

Name | Access | Summary |
---|---|---|

AddCriteria() : Void | public | |

AddCriteria() : Void | public | |

AddCriterionRatedChoices() : Void | public | |

AddCriterionRatedChoices() : Void | public | |

CalculateModel() : Void | public | |

ExpandUtility() : GeneralMatrix | public | ( |

Name | Access | Summary |
---|---|---|

Constants() | public | Initializes a new instance of the class. |

Name | Access | Summary |
---|---|---|

randomIndices : Double[] | public |

Name | Access | Summary |
---|

`public class PrioritiesSelector`

This class implements the Saaty's method for estimating eigenvalues of the priorities matrix.

Name | Access | Summary |
---|---|---|

PrioritiesSelector() | public | Initializes a new instance of the class. |

Name | Access | Summary |
---|---|---|

CalculatedMatrix : GeneralMatrix | public | Final matrix of n by 1 containing results of the selection |

Consistency : Double | public | Consistency of the selection |

ConsistencyRatio : Double | public | Consistency ratio of CI/RI |

LambdaMax : Double | public | Estimate of the max eigenvalue |

Name | Access | Summary |
---|---|---|

ComputePriorities() : Void | public | Calculates priorities using the Saaty method |

PCalc() : Void | public | Average values of the priority matrix over sum of columns. set values of sum of averaged rows into a new matrix |