Risikoanalyse -Tool für Java -Entwickler

Risikoanalyse ausführen

Aspose.Tasks FÜR JAVA API unterstützt die Durchführung der Risikoanalyse in einer Projektdatendatei. Dies basiert auf der Monte -Carlo -Simulation, die unterschiedliche Wahrscheinlichkeitsverteilungen und Korrelationen unterstützt. Die RiskAnalyzer -Klasse kann verwendet werden, um die Risikoanalyse durchzuführen, die auf einem Projektplan basiert (Aufgabendauer und deren Start-/Enddaten). Ein Projekt Finish kann also die Ausgabe einer solchen Analyse sein. Das folgende Beispiel zeigt diese Funktionalität Schritt für Schritt.

1. Vorbereitung der Analyseeinstellungen

// For complete examples and data files, please go to https://github.com/aspose-tasks/Aspose.Tasks-for-Java
RiskAnalysisSettings settings = new RiskAnalysisSettings();
// set a number of iterations for Monte Carlo simulation (the default value is 100).
settings.setIterationsCount(200);

2. Identifying the Input of Analysis

// For complete examples and data files, please go to https://github.com/aspose-tasks/Aspose.Tasks-for-Java
Project project = new Project("NewProductDev.mpp"); // attached test project

// Initialize a risk pattern
Task task = project.getRootTask().getChildren().getById(14);

RiskPattern pattern = new RiskPattern(task);
// Select a distribution type for the random number generator to generate possible values from (only two types currently supported, namely normal and uniform)
// note that the normal distributions are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known,
// thus this distribution is set to default (for more details see here: https://en.wikipedia.org/wiki/Normal_distribution)
pattern.setDistribution (ProbabilityDistributionType.Normal);
// Set the percentage of the most likely task duration which can happen in the best possible project scenario
// (the default value is 75, which means that if the estimated specified task duration is 4 days then the optimistic duration will be 3 days)
pattern.setOptimistic(70);
// Set the percentage of the most likely task duration which can happen in the worst possible project scenario
// (the defaut value is 125, which means that if the estimated specified task duration is 4 days then the pessimistic duration will be 5 days.).
pattern.setPessimistic(130);
// Set a confidence level that correspond to the percentage of the time the actual values will be within optimistic and pessimistic estimates.
// You can think of it as a value of standard deviation: the more uncertain about your estimates you are, the more the value of standard deviation used in random number generator is
pattern.setConfidenceLevel(ConfidenceLevel.CL75);

// you can add as many risk patterns as needed to model expected project risks
settings.getPatterns().add(pattern);

3. Analyze the Risks

RiskAnalyzer analyzer = new RiskAnalyzer(settings);
RiskAnalysisResult analysisResult = analyzer.analyze(project);

4. Use the Results of the Analysis

// For complete examples and data files, please go to https://github.com/aspose-tasks/Aspose.Tasks-for-Java
//Select the desired output (here we get early finish of the root task)
RiskItemStatistics rootEarlyFinish = analysisResult.getRiskItems(RiskItemType.EarlyFinish).get(project.getRootTask());

System.out.println("Expected value: "+ rootEarlyFinish.getExpectedValue());
System.out.println("StandardDeviation: " + rootEarlyFinish.getStandardDeviation());
System.out.println("10% Percentile: " +rootEarlyFinish.getPercentile(10));
System.out.println("50% Percentile: " + rootEarlyFinish.getPercentile(50));
System.out.println("90% Percentile: " + rootEarlyFinish.getPercentile(90));
System.out.println("Minimum: " + rootEarlyFinish.getMinimum());
System.out.println("Maximum: " + rootEarlyFinish.getMaximum());

// Also pdf report can be saved (it is rendered for Project Root Task Finish date):
analysisResult.saveReport("AnalysisReport.pdf");