Excel Solver Tutorial for Optimization Users

Using Excel Solvers for Optimization

Welcome to our tutorial about Solvers in Excel -- the easiest way to solve optimization problems -- from Frontline Systems, developers of the Solver in Microsoft Excel.  You can solve the step-by-step linear programming example below using Excel alone -- but if you need to solve problems with more than 200 variables, consider our Excel Solver upgrades. 

• What are Solvers Good For?
• What Must I Do to Use a Solver?
• How Do I Define a Model?
• What Kind of Solution Can I Expect?
• What Makes a Model Hard to Solve?
• Can You Show Me Step by Step? 

After completing this tutorial, you can learn more about topics such as linearity versus nonlinearity and sparsity in optimization models by taking our advanced tutorial.  If you'd like to learn more about simulation as well as optimization, consult our tutorials on risk analysis and Monte Carlo simulation.

What are Solvers Good For?

Solvers, or optimizers, are software tools that help users find the best way to allocate scarce resources. The resources may be raw materials, machine time or people time, money, or anything else in limited supply. The "best" or optimal solution may mean maximizing profits, minimizing costs, or achieving the best possible quality.  An almost infinite variety of problems can be tackled this way, but here are some typical examples:

Finance and Investment

• Working capital management involves allocating cash to different purposes (accounts receivable, inventory, etc.) across multiple time periods, to maximize interest earnings.
• Capital budgeting involves allocating funds to projects that initially consume cash but later generate cash, to maximize a firm's return on capital.
• Portfolio optimization -- creating "efficient portfolios" -- involves allocating funds to stocks or bonds to maximize return for a given level of risk, or to minimize risk for a target rate of return.

Manufacturing

• Job shop scheduling involves allocating time for work orders on different types of production equipment, to minimize delivery time or maximize equipment utilization.
• Blending (of petroleum products, ores, animal feed, etc.) involves allocating and combining raw materials of different types and grades, to meet demand while minimizing costs.
• Cutting stock (for lumber, paper, etc.) involves allocating space on large sheets or timbers to be cut into smaller pieces, to meet demand while minimizing waste.

Distribution and Networks

• Routing (of goods, natural gas, electricity, digital data, etc.) involves allocating something to different paths through which it can move to various destinations, to minimize costs or maximize throughput.
• Loading (of trucks, rail cars, etc.) involves allocating space in vehicles to items of different sizes so as to minimize wasted or unused space.
• Scheduling of everything from workers to vehicles and meeting rooms involves allocating capacity to various tasks in order to meet demand while minimizing overall costs.

Next: What Must I Do to Use a Solver? >

Our Premium Solver Platform works with existing Excel Solver models, solves much larger problems up to hundreds of times faster, and solves new kinds of problems via Evolutionary Solver. Solver Engines plug into the Premium Solver Platform.

Solver Platform SDK makes it easy to solve any type or size of optimization problem in your Visual Basic, VB.NET, C/C++, C#, Java, or MATLAB program. And it's easy to deploy your application with our flexible licensing for software vendors and corporate developers.

Risk Solver is the easiest, fastest, most powerful tool you can buy for risk analysis of your Excel models, using Monte Carlo simulation. Evaluate thousands of scenarios in seconds, and see instantly updated charts and statistics, each time you ask "what if".

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