Other names for a decision matrix include decision grid, problem selection matrix, Pugh matrix, solution matrix, grid analysis, weighted decision matrix, criteria rating form, and criteria-based matrix.
decision grid demo download
You can use our decision matrix template to get started quickly. Or you can fiddle around drawing clumsy grids in Powerpoint if you want everyone to roll their eyes and snigger at your awkward attempts to make it look professional. Your choice.
This article assumes you have at least intermediate-level programming skills and a vague idea of what Sudoku puzzles are, but does not assume you know anything about constraint satisfaction problems or the MSF library. The demo program is coded using C# but you should be able to refactor the demo to other .NET languages without too much trouble. All the code is presented here and it is also available in the code download that accompanies this article at msdn.microsoft.com/magazine/msdnmag0814. All normal error checking has been removed to keep the main ideas clear.
The grid object is an array-of-arrays style matrix where each cell is a Decision object. You can think of a Decision object as an encapsulation of an answer. Or put another way, to solve a Sudoku puzzle you need to determine 9 x 9 = 81 values. Each of these values is represented by a Decision object and the demo stores them in a matrix.
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Another effective decision-making matrix to identify a range of favorable alternatives from the costly, unprofitable, or distressing ones is shown in this Yes/No decision matrix design. Align your projects, track their efficacy, and finally signal the ones that are good to go. Go ahead and download this utility now!
The Hello World example decision set demonstrates how to insert objects into the decision engine working memory, how to match the objects using rules, and how to configure logging to trace the internal activity of the decision engine.
The State example decision set demonstrates how the decision engine uses forward chaining and any changes to facts in the working memory to resolve execution conflicts for rules in a sequence. The example focuses on resolving conflicts through salience values or through agenda groups that you can define in rules.
This example demonstrates how to use the PropertyChangeSupport interface to avoid the need for explicit modify statements in the rules. To make use of this interface, ensure that your facts implement PropertyChangeSupport in the same way that the class org.drools.example.State implements it, and then use the following code in the DRL rule file to configure the decision engine to listen for property changes on those facts:
The Fibonacci example decision set demonstrates how the decision engine uses recursion to resolve execution conflicts for rules in a sequence. The example focuses on resolving conflicts through salience values that you can define in rules.
As the example spreadsheet demonstrates, you can use only the first tab of a spreadsheet to create decision tables, but multiple tables can be within a single tab. Decision tables do not necessarily follow top-down logic, but are more of a means to capture data resulting in rules. The evaluation of the rules is not necessarily in the given order, because all of the normal mechanics of the decision engine still apply. This is why you can have multiple decision tables in the same tab of a spreadsheet.
The Pet Store example decision set demonstrates how to use agenda groups and global variables in rules and how to integrate Red Hat Decision Manager rules with a graphical user interface (GUI), in this case a Swing-based desktop application. The example also demonstrates how to use callbacks to interact with a running decision engine to update the GUI based on changes in the working memory at run time.
The Sudoku example decision set, based on the popular number puzzle Sudoku, demonstrates how to use rules in Red Hat Decision Manager to find a solution in a large potential solution space based on various constraints. This example also shows how to integrate Red Hat Decision Manager rules into a graphical user interface (GUI), in this case a Swing-based desktop application, and how to use callbacks to interact with a running decision engine to update the GUI based on changes in the working memory at run time. 2ff7e9595c
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