Create a Linear Programming Module:

Data: NEX tuition reimbursement agreements

• $5,250/ year, must be used towards a 4 year college that will enhance your current role
• The price per year includes: Classes (3 credit hours per class) , Books, and fees
• No limit on how long the college degree takes you to finish.
• You pay for the college upfront, get reimbursed after the grades are submitted.

Notes:

Building a Linear Programming (LP) model to optimize college reimbursement from your employer involves defining the objective, decision variables, constraints, and the LP model structure. The goal is to maximize the value of the education you receive while staying within budget constraints. Here's a step-by-step guide to building such a model:

1. **Define the Objective Function:**

- The objective to maximize the total number of credit hours

- Assign a numerical value to your objective, depending on the metric you choose to maximize.

2. **Identify Decision Variables:**

- Define the decision variables that you can control. In this case, you may consider variables such as:

- X1: Number of credit hours to take in each semester.

- X2: Courses to take in each semester.

- X3: The amount spent on books and materials.

3. **Set Constraints:**

- Constraints represent the limitations and conditions that your model must satisfy.

- Budget Constraint: Your employer will likely have a budget limit for your education $5,250

- Budget constraint: X1*(UHD CR per HR =245.75) + X3 Total Reimbursement Limit

- Time Constraint: Consider the duration or timeline for your education. You might want to complete your degree within a specific number of years. Could this be the

==> Semester constraint: X1 Maximum credit hours per semester

- Yearly constraint: X1 over all semesters Maximum years*Number of semesters per year

- Course Load Constraint: Ensure that you don't take too many or too few courses in each semester.

- Course load constraint: Minimum Courses per semester X2 Maximum Courses per semester

4. **Modeling the Objective Function:**

- Based on your objective maximize the total number of credit hours ,and create a linear expression using your decision variables and the chosen metric.

5. **Solve the LP Model:**

- Utilize LP solver software like Excel Solver or specialized LP software to find the optimal solution.

6. **Interpret the Results:**

- Review the LP model results to determine the best course of action based on your objective and constraints.

7. **Sensitivity Analysis:**

- It's important to analyze how changes in parameters, such as the budget limit or credit hours' cost, impact your optimal solution.

8. **Implement the Plan:**

- Once you've determined the optimal education plan, work with your employer's reimbursement program to ensure that your education expenses are covered according to the model's recommendations.

Remember that this LP model is a simplified representation of the real world. It assumes a fixed tuition cost, stable credit hours per semester, and other simplifications. You might need to adjust the model as your real-world circumstances change. Also, consult with your employer's HR or finance department to understand the specifics of their reimbursement program and policies.