How to Use WhatsOptimal LP System Student Version: Step-by-Step TutorialWhatsOptimal LP System Student Version is built to help students learn linear programming (LP) modeling, solve optimization problems, and visualize results in an accessible environment. This step-by-step tutorial walks you through installation (if required), the user interface, creating models, running solvers, interpreting outputs, and best practices to get the most from the Student Version.
1. What the Student Version includes (quick overview)
- Model editor for creating LP formulations (variables, objective, constraints).
- Prebuilt templates for common LP problems (diet, transportation, assignment, production).
- Solver adapted for classroom-sized problems (often limited in variables/constraints compared to professional editions).
- Result viewer with tables and basic charts to inspect variable values and objective.
- Export options (CSV or PDF) for reporting homework.
- Help and tutorials integrated inside the app.
2. System requirements & installation
- Check requirements: most student builds run on Windows, macOS, and popular Linux distributions. Ensure you have at least 4 GB RAM and 200 MB free disk space.
- Download the Student Version from your institution’s portal or the official WhatsOptimal website (use the link your instructor provided).
- Install following the platform-specific installer. On macOS, allow the app in Security & Privacy if blocked. On Windows, run the installer as an administrator if you encounter permission errors.
- Launch the app and sign in if required (student license key or institutional single sign-on).
3. Overview of the interface
- Top menu: File, Edit, Model, Solve, View, Help.
- Left panel: Model tree — lists variables, objectives, and constraints.
- Center: Model editor — text or form-based input for the LP.
- Right panel: Properties/Inspector — shows details for the selected item.
- Bottom: Console/log and solution summary after running the solver.
Tip: Toggle between text-mode and form-mode when editing models. Text-mode is faster for experienced users; form-mode helps beginners avoid syntax errors.
4. Building a model: step-by-step
- Create a new project (File → New → LP Project). Give it a name relevant to your homework.
- Define decision variables:
- In form-mode: click “Add Variable,” name it (e.g., x1), choose type (Continuous, Integer, Binary), and set bounds (lower/upper).
- In text-mode, use the app’s modeling language. Example:
var x1 >= 0; var x2 >= 0;
- Set the objective:
- Choose Maximize or Minimize.
- Enter the objective expression. Example:
maximize Z: 3*x1 + 5*x2;
- Add constraints:
- Use “Add Constraint” for each condition. Give each a name (c1, c2).
- Example constraints:
c1: 2*x1 + 3*x2 <= 100; c2: x1 + x2 <= 40;
- Save the model.
Example complete model (text-mode):
var x1 >= 0; var x2 >= 0; maximize Z: 3*x1 + 5*x2; subject to c1: 2*x1 + 3*x2 <= 100; c2: x1 + x2 <= 40; 5. Running the solver
- Select the solver type (default Student Solver). Some student versions let you choose simplex, interior-point, or mixed-integer heuristic solvers.
- Set solver options (time limit, tolerance). For classroom problems, default options usually suffice.
- Click “Solve.” The console will show progress and final status (Optimal, Infeasible, Unbounded, or Feasible).
- If the solver reports issues (infeasible/unbounded), use the infeasibility diagnostics tool (if available) or check constraints for contradictions or missing bounds.
6. Interpreting results
- Solution summary shows objective value and status. Optimal status indicates a verified best solution under current model.
- Variable table lists values, reduced costs (for linear problems), and bounds.
- Constraint table shows shadow prices (dual values) and slack — useful for sensitivity analysis.
- Charts: basic bar or line charts to visualize variable levels or objective composition.
Example interpretation:
- If x1 = 20, x2 = 20, objective Z = 160, you can explain what those decision variable levels mean in the context of your problem (e.g., produce 20 units of product A and 20 of B).
7. Sensitivity and what-if analysis
- Use built-in sensitivity report to see how objective coefficients and right-hand-sides can change without altering the optimal basis.
- Perform scenario runs: duplicate the model, change parameters (e.g., resource availability), and re-solve to compare outcomes.
- Use parameter sweep (if included) to run multiple cases automatically and export results to CSV.
8. Common issues & troubleshooting
- Syntax errors in text-mode: switch to form-mode to correct variable names and symbols.
- Infeasible model: relax bounds temporarily or check each constraint for errors. Consider adding slack variables to diagnose.
- Large models exceed student limits: simplify the model (aggregate variables) or request instructor access to a full license.
- Solver hangs or runs slowly: reduce tolerances or apply presolve options.
9. Tips for classroom success
- Start with a clear mathematical formulation on paper: decision variables, objective, constraints.
- Name variables and constraints meaningfully (produce_x, cap_week1).
- Use templates for common problem types and adapt them.
- Keep models modular: group related constraints or variables so debugging is easier.
- Export results and include model text in your submission so instructors can reproduce your work.
10. Exporting and sharing results
- Export solution tables to CSV for spreadsheets.
- Export model and results as PDF for reports.
- Save model files (.woproj or the app’s native extension) to share with classmates or instructors.
11. Example: full walkthrough (small production problem)
- New project → name “FactoryLP.”
- Add continuous variables: x_A >=0, x_B >=0.
- Objective: maximize 40*x_A + 50*x_B.
- Constraints:
- 3*x_A + 2*x_B <= 180 (Material)
- 1*x_A + 2*x_B <= 80 (Labor)
- Solve → status Optimal, x_A = 20, x_B = 30, Objective = 2300.
- Generate sensitivity report and export CSV with variable values.
12. Additional learning resources
- Built-in tutorials and example library.
- Linear programming textbooks or lecture notes recommended by your course.
- Instructor or TA office hours for license or capacity questions.
If you want, I can: convert the example model into the exact modeling syntax used by your WhatsOptimal Student Version (tell me whether you use text-mode language or form-mode), or create a sample assignment-ready PDF with model, solution, and interpretation.
Leave a Reply