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4 Estimating Risk Adjusted Cost or Schedule Using Fuzzy Logic
Author(s) -
Bellagamba Laurence
Publication year - 1999
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.1999.tb00166.x
Subject(s) - schedule , fuzzy logic , computer science , function (biology) , reliability engineering , risk analysis (engineering) , operations research , mathematics , artificial intelligence , engineering , business , operating system , evolutionary biology , biology
A method is presented to quickly and inexpensively obtain risk adjusted cost or schedule estimates so many system implementation options can be compared to find the best performer for a given cost. Cost or schedule consequences are modeled as a function of technical maturity and proposal risk. Technical maturity assesses how much of the system already exists. Proposal risk assess the uncertainty of of the cost and schedule estimates. Fuzzy logic is used as an alternative to probability to estimate the risk adjusted cost and schedule. Using fuzzy logic reduces the time required to interview and interpret domain expert's assessments of risk sources and consequences, while still capturing any uncertainty in the expert's opinion. Using fuzzy logic provides a single number for risk adjusted cost or schedule that does not require interpreting a cumulative probability density function.