The Bound branch is not viewable in Figure 3. In the actual file, this branch appears in sequence following the Constraints branch in the Model tree. The solution provided to this problem is not the optimal solution. That is, the solver had reached a maximum time constraint set for the engine and automatically prompted us to choose if we would like to stop. Given that the best possible solution (shown in the bottom of the output tab) was 1.28, and the current solution of 1.301, a decision was made to stop the search because the solution provided was deemed strong enough. Parameter equating is made possible because of the linking structure employed in the original administration. Solution times will also vary depending on which Solver engine is used. For the most part, more expensive engines can be expected to result in faster solution times. The total onetime cost of the configuration used to solve each of the examples in this demonstration is $9325. Academic discounts are available for professors and students. Further, the configuration used in this paper is more sophisticated than is required for most test assembly problems. Users are encouraged to contact Solver support to determine the configuration that best suits their specific optimization needs. For example, the problems in this paper could have been solved with a configuration costing $6490. This configuration would have lead to slightly slower solution times. For a complete price list visit Citation (2009). Three Applications of Automated Test Assembly within a User-Friendly Modeling Environment. Practical Assessment, Research & Evaluation, 14(14). Available online: . Corresponding Author Ken Cor Stanford University Palo Alto, CA Email: kcor [at] Stanford.edu APPENDIX A Mathematical Model for Example 1 The decision variable for this problem (and for the remaining problems in this investigation) is represented by equation A1. (A1) The decision variable is constrained so that it can only take the form of a one or a zero. Within the excel framework this constraint can be accomplished by using equation A2. (A2) The following multiple test level constraints (as generalized by equation A3) ensure that each item, i, can only be used for one test, t, i.e. no item overlap. This general expression results in 55 constraints. for all i (A3) There are 12 content constraints (4 categories x 3 forms) that are used to restrict the total number of items in each content category, Vc, to the corresponding specification, CSpec, for each test (equation A4).
The Bound branch is not viewable in Figure 3. In the actual file, this branch appears in sequence following the Constraints branch in the Model tree. The solution provided to this problem is not the optimal solution. That is, the solver had reached a maximum time constraint set for the engine and automatically prompted us to choose if we would like to stop. Given that the best possible solution (shown in the bottom of the output tab) was 1.28, and the current solution of 1.301, a decision was made to stop the search because the solution provided was deemed strong enough. Parameter equating is made possible because of the linking structure employed in the original administration. Solution times will also vary depending on which Solver engine is used. For the most part, more expensive engines can be expected to result in faster solution times. The total onetime cost of the configuration used to solve each of the examples in this demonstration is $9325. Academic discounts are available for professors and students. Further, the configuration used in this paper is more sophisticated than is required for most test assembly problems. Users are encouraged to contact Solver support to determine the configuration that best suits their specific optimization needs. For example, the problems in this paper could have been solved with a configuration costing $6490. This configuration would have lead to slightly slower solution times. For a complete price list visit Citation (2009). Three Applications of Automated Test Assembly within a User-Friendly Modeling Environment. Practical Assessment, Research & Evaluation, 14(14). Available online: . Corresponding Author Ken Cor Stanford University Palo Alto, CA Email: kcor [at] Stanford.edu APPENDIX A Mathematical Model for Example 1 The decision variable for this problem (and for the remaining problems in this investigation) is represented by equation A1. (A1) The decision variable is constrained so that it can only take the form of a one or a zero. Within the excel framework this constraint can be accomplished by using equation A2. (A2) The following multiple test level constraints (as generalized by equation A3) ensure that each item, i, can only be used for one test, t, i.e. no item overlap. This general expression results in 55 constraints. for all i (A3) There are 12 content constraints (4 categories x 3 forms) that are used to restrict the total number of items in each content category, Vc, to the corresponding specification, CSpec, for each test (equation A4).
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