How to Use Solver in Excel

Solver is an Excel add-in that finds the best values for several input cells at once, subject to limits you set. You choose an objective cell to maximize, minimize, or hit a target, list the cells Solver may change, and add constraints. In financial models it handles allocation, scheduling, and mix problems that have too many moving parts for Goal Seek.

What Solver does and when to use it

Solver optimizes one objective cell by adjusting many changing cells while respecting a set of constraints. Where Goal Seek solves one equation in one unknown, Solver tackles a system with multiple variables and rules at the same time.

Use it when you must allocate a fixed budget across projects for the highest return, set a product mix within capacity limits, or minimize cost while meeting demand. If your problem reads as maximize or minimize something subject to a list of conditions, Solver is the right tool.

Step by step

First confirm the add-in is loaded. Go to File > Options > Add-ins, choose Excel Add-ins in the Manage box, click Go, then check Solver Add-in. It then appears on the Data tab.

1. Go to Data > Solver to open the dialog.
2. Set Objective to the result cell, for example B12.
3. Choose Max, Min, or Value Of and a number if hitting a target.
4. In By Changing Variable Cells, select the inputs, for example B2:B6.
5. Click Add under Subject to the Constraints to enter each rule.
6. Pick a Solving Method, then click Solve and keep or discard the result.

Constraints are the rules Solver must respect while it searches for the best objective value.

A model use case

Allocate a marketing budget across five channels to maximize forecast revenue. The objective cell sums modeled revenue, the changing cells are the spend per channel, and constraints cap total spend and set a minimum per channel.

Solver returns a spend plan that respects every rule. Because it rewrites the changing cells, run it on a copy of the model or record the starting inputs so you can compare scenarios.

• One objective, many changing cells, many constraints.
• Pick Simplex LP for linear problems and GRG Nonlinear for smooth curves.
• Solver overwrites the changing cells, so save the originals first.

Pitfalls and limits

Solver can stop at a local solution rather than the true best one, especially with nonlinear models, so try different starting values to test stability. Poorly scaled inputs, where one cell is in millions and another in fractions, can also throw it off; the Use Automatic Scaling option in the Solver Options helps.

The bundled engine caps the number of variables and constraints, and it will report that it could not find a feasible solution when constraints conflict. Always sanity check the answer against the model logic before you trust it.