Excel Solver is an advanced tool that helps users solve optimization problems by finding the optimal value (maximum or minimum) for a formula in a single cell, known as the objective cell, based on constraints applied to other cells in the spreadsheet. It is widely used in decision-making scenarios such as resource allocation, financial modeling, and operations management.

In this article, you will learn what Excel Solver is, how to set it up, and how to use it to solve complex problems efficiently.

Required Tools

The tutorial is specifically made for any version of Microsoft Excel. The same steps should work with Google Sheets with some minor changes.

What is Excel Solver?

Excel Solver is an add-in provided by Microsoft Excel that allows you to define an objective and a set of constraints to optimize your desired outcome. Solver is capable of handling linear and nonlinear models, and can work with multiple variables.

Solver is best used in scenarios such as:

• Maximizing or minimizing profit or cost.
• Allocating resources efficiently.
• Solving scheduling problems.
• Balancing a budget.

How to Enable Excel Solver

By default, Solver is not active in Excel. You need to activate it first.

• Go to the File Tab: Click on File and then select Options.
• Click on Add-ins: On the left-hand side, click Add-ins.
• Manage Excel Add-ins: At the bottom, you’ll find the Manage drop-down. Select Excel Add-ins and click Go.
• Enable Solver: In the dialog box that appears, check the box next to Solver Add-in, and click OK.

Once Solver is enabled, you’ll see it under the Data tab in the Analyze group.

Understanding the Components of Solver

Before diving into how to use Solver, it’s important to understand its core components:

• Objective Cell: This is the cell that you want to optimize. You can either maximize, minimize, or set it to a specific value.
• Variable Cells (Changing Cells): These are the cells that Solver will change to achieve the result in the objective cell.
• Constraints: These are conditions or limitations that you impose on the problem. For example, the budget should not exceed a certain amount or a resource limit must be maintained.
• Solver Parameters Dialog Box: This is where you set up your problem by defining the objective, changing cells, and constraints.

How to Use Excel Solver: Step-by-Step Guide

Step 1: Define the Problem

Let’s say you’re managing a small manufacturing company, and you want to maximize profit by deciding how many units of two different products to produce. You have constraints like limited labor hours and materials.

Your data might look something like this:

Product	Profit per Unit	Labor Hours per Unit	Material per Unit
Product A	$30	2	3
Product B	$50	4	2
Total Available		100 hours	90 units

Our goal is to maximize profit.

Firstly, let us put this problem in a spreadsheet. Let’s now add three separate columns for 1) Units to be Produced, 2) Total Labor Hours (Unit to be Produced x Labor Hours per Unit), and 3) Total Materials (Unit to be Produced x Material per Unit).

Step 2: Set Up the Objective

1. Insert Formulas: In a separate cell, create a formula that calculates the total profit based on the number of units produced for each product. In the example case, in J2, let’s enter =D3C3+D4C4.

2. Go to the Solver Dialog Box: Under the Data tab, click Solver.
3. Set the Objective: In the Set Objective field, enter the cell reference for total profit (e.g., J3). Select Max to maximize the value.

Step 3: Define the Changing Variables

In the By Changing Variable Cells field, select the cells that represent the decision variables. Here, as cells C3 and C4 represent the number of units to produce, we will put $C$3:$C$4.

Step 4: Add Constraints

• Click Add: In the Solver Parameters window, click Add to add constraints.
• Add Labor Hours Constraint: Select the sum of labor hours used (F5), and ensure that the sum of labor used does not exceed the total available (e.g., 100 hours). You can add the constraint as <= 100.
• Add Material Constraint: Similarly, add a constraint for materials used, which would be H5 <= 90.

Step 5: Solve the Problem

• Click Solve: Once all parameters are set, click the Solve button. Solver will process the problem and provide a solution. If it finds a feasible solution, it will display the results.
• Review Results: Choose to either keep the solution or revert to the original values. Solver also offers reports that can provide detailed insights into how it solved the problem.

Download the Practice File

Solver Options: Understanding the Algorithms

Solver offers three different solving methods based on the nature of your optimization problem:

• Simplex LP: This method is used for linear programming problems, where all equations and constraints are linear.
• GRG Nonlinear: This is used for nonlinear problems where some relationships are nonlinear.
• Evolutionary: This method is used for complex, non-smooth problems that cannot be solved using linear or nonlinear methods.

Common Applications of Solver

• Resource Allocation: Allocating limited resources (like raw materials, labor, or budget) to maximize output or minimize cost.
• Financial Modeling: Solver is used in financial scenarios to optimize profit, minimize risk, or balance portfolios under constraints.
• Scheduling: In operations management, Solver can help schedule production or assign tasks in a way that maximizes efficiency.
• Supply Chain Optimization: In logistics, Solver can help minimize transportation costs while meeting demand.

Solver Tips and Best Practices

• Start Simple: Begin with a basic setup to ensure that Solver can find a feasible solution before adding more complexity.
• Use Sensible Constraints: Avoid overly restrictive constraints, as they may prevent Solver from finding a solution.
• Use Solver Reports: After running Solver, generate and review reports to gain insights into how the problem was solved and if the solution is optimal.
• Use Bounds for Variables: Define upper and lower bounds for your changing cells to prevent unrealistic results.

Limitations of Solver

• Local Solutions: Solver may sometimes find a local optimum instead of a global optimum, especially in nonlinear problems.
• Scalability: Solver works well with small to medium datasets but may struggle with very large datasets.
• Complexity: Solver can struggle with problems that have too many constraints or involve non-smooth functions.

Conclusion

Excel Solver is a powerful tool that can help you solve complex decision-making problems across a range of industries. By understanding how to set up an optimization problem and properly using constraints and variables, you can leverage Solver to find the best possible solutions for resource allocation, financial planning, and more. With practice, you’ll be able to handle increasingly complex problems with ease.

If you have any questions or need more assistance, feel free to reach out in the comments or through our contact page.