Microsoft Excel Solver Routine

The first thing to note is that the Solver routine is not automatically installed when Excel is installed. In order to install the Solver routine a you must perform custom installation or install the routine specifically after the standard installalion. We suspect you are now wondering where you put your Microsoft installation disks. The Solver routine is found on the Excel main menu toolbar under Tools. 

Let us now reconsider the example in Section 6.10.1, and use the Solver routine to find the solution. The problem will initially be set up in the same manner that would traditionally be used in optimization that is the constraints will be written as inequality constraints as shown in Equation 6.22. Table 6.7 shows the initial Excel file under the colunms headed by Results with Initial Guesses and it is also available on the website www.taylorandfrancis.com under the file name optimization.xls. Note that 

1 Engineering Design with Polymers and Composites, 2nd Edition  

28 Check Eula and Johnson Buckling (stress failure is part of Johnson )  

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Linear and nonlinear programming solvers have been interfaced to spreadsheet software for desktop computers. The spreadsheet has become a popular user interface for entering and manipulating numeric data. Spreadsheet software increasingly incorporates analytic tools that are accessible from the spreadsheet interface and permit access to external databases. For example, Microsoft Excel incorporates an optimization-based routine called Solver that operates on the values and formulas of a spreadsheet model. Current versions (4.0 and later) include LP and NLP solvers and mixed integer programming (MIP) capability for both linear and nonlinear problems. The user specifies a set of cell addresses to be independently adjusted (the decision variables), a set of formula cells whose values are to be constrained (the constraints), and a formula cell designated as the optimization objective. 

This should first be done for the experimental data and then, on the same graph, for an assumed value of b, the mean thickness of the amorphous layers. A sensible value to assume is 5-10 nm. This value can then be refined manually, by adjusting the value until a visually, good fit to the data is obtained. Alternatively a least-squares fit can be done, again by manual adjustment or by using a fitting routine such as the Solver tool in Microsoft Excel. The best fit is found for A = 8.1 nm and the graph shows the fit. 

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