Risk Solver Platform

Risk Solver Platform from Frontline Systems combines all the capabilities of Premium Solver Platform for optimization, Risk Solver Pro for simulation, and several powerful methods for optimization of uncertain models.

Premium Solver Platform and Premium Solver Pro for optimization, and Risk Solver Pro for simulation and simulation-optimization are available as subsets of Risk Solver Platform. All these products use one set of program files, and share a common user interface; the product you ‘experience’ is determined by your license code.

  • Premium Solver Platform – Premium Solver Platform is Frontline’s most powerful product for conventional optimization. It includes the PSI Interpreter, five built-in Solvers (LP/Quadratic, SOCP Barrier, LSGRG Nonlinear, Interval Global, and Evolutionary), and it supports plug-in large-scale Solver Engines. It has no Monte Carlo simulation, simulation optimization, stochastic programming or robust optimization.
  • Premium Solver Pro – Premium Solver Pro is Frontline’s basic upgrade for the standard Excel Solver, for conventional optimization. It includes a Simplex LP Solver, GRG Nonlinear Solver, Evolutionary Solver, Branch & Bound method for integer and all different constraints, and the Multi-start method for global optimization.
  • Risk Solver Pro – Risk Solver Pro is Frontline’s full-function product for Monte Carlo simulation. It includes all of the simulation functionality of Risk Solver Platform including the Psi Interpreter for simulations. Problem size limits in combination with Premium Solver Pro are 500 decision variables and 250 constraints. Problem size limits in combination with Premium Solver Platform are 1000 decision variables and 1000 constraints.

Risk Solver Platform works with any 32-bit version of Microsoft Excel.


Consider the following problem. Our factory is building three products: TV sets, stereos and speakers. Each product is assembled from parts in inventory, and there are five types of parts: chassis, picture tubes, speaker cones, power supplies and electronics units. Our goal is to produce the mix of products that will maximize profits, given the inventory of parts on hand.

The Algebraic Form – The problem can be described in algebraic form as follows. The decision variables are the number of products of each type to build: x1 for TV sets, x2 for stereos and x3 for speakers. There is a fixed profit per unit for each product, so the objective function (the quantity we want to maximize) is:

Maximize 75 x1 + 50 x2 + 35 x3 (Profit)

Building each product requires a certain number of parts of each type. For example, TV sets and stereos each require one chassis, but speakers don’t use one. The number of parts used depends on the mix of products built (the left hand side of each constraint), and we have a limited number of parts of each type on hand (the corresponding constraint right hand side)

Subject to

1 x1 + 1 x2 + 0 x3 <= 400 (Chassis)

1 x1 + 0 x2 + 0 x3 <= 200 (Picture tubes)

2 x1 + 2 x2 + 1 x3 <= 800 (Speaker cones)

1 x1 + 1 x2 + 0 x3 <= 400 (Power supplies)

2 x1 + 1 x2 + 1 x3 <= 600 (Electronics)

Since the number of products built must be nonnegative, we also have the constraints x1, x2, x3 >= 0. Note that terms like 0 x3 are included purely to show the structure of the model – they can be either omitted or included when entering formulas in Excel.

The Spreadsheet Formulas – The fastest (though not necessarily the best) way to lay out this problem on the spreadsheet is to pick (for example) cell A1 for x1, cell A2 for x2 and cell A3 for x3. Then the objective can be entered in cell A4, much like the algebraic form above:

A4: =75*A1+50*A2+35*A3

We can go on to enter a formula in (say) cell B1 for the first constraint left hand side (Chassis) as =1*A1+1*A2+0*A3, or the simpler form:

B1: =A1+A2

Similarly, we can use cell B2 for the formula =A1 (Picture tubes), B3 for the formula =2*A1+2*A2+A3 (Speaker cones), B4 for the formula =A1+A2 (Power supplies), and B5 for the formula =2*A1+A2+A3 (Electronics):

B2: =A1

B3: =2*A1+2*A2+A3

B4: =A1+A2

B5: =2*A1+A2+A3

Finally, we’ll enter the constraint right hand side values in cells C1:C5:

C1: 400

C2: 200

C3: 800

C4: 400

C5: 600

We now have a simple spreadsheet model that we can use to play ‘what if.’ For any values we enter for the decision variables in cells A1, A2 and A3, the objective (Total Profit) and the corresponding values of the constraint left hand sides (the numbers of parts used) will be calculated.

We want to turn this ‘what if’ spreadsheet model into an optimization model, where the Solver will automatically find optimal values for the cells A1:A3, so that the objective function at A4 is maximized, and the constraints are satisfied.

Analyzing Uncertainty and Model Assumptions
Simple Linear Regression

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