Example Models to Perform Risk and Decision Analysis using Palisade Software

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All example models may be downloaded, modified, and distributed free of charge. You can use these as inspiration for your own models.

Please note all examples require @RISK or the appropriate DecisionTools software product installed to see the full analysis.

Legal Notice: Palisade assumes no liability for your use (or inability to use) any of these examples. All models are provided as-is without warranty of any kind, and by downloading them you assume all risk for the use of and/or results generated from these models.

Progress Units Through Stages Over Time

This example looks at a process with 5 stages that handle units over a period of a year. Units could represet sales opportunities, hiring canditates, chemical compounds, etc. We are interested in determining the probability of reaching a yearly target of units arriving at Stage 5 given the ...

Navigating the German IDW PS340 Regulation with @RISK

This case study illustrates a potential implementation of regulatory requirements to quantify the probability of business continuity. It demonstrates a potential quantification of operating and risk register (low probability/high impact) risks and their impact on the balance sheet and the ...

Decision Trees in Rock Engineering

This file contains 3 decision tree examples from the Rock Engineering field. They illustrate typical single-stage decision problems You will find 3 decision trees in the model: Debris flow containment Rock slope stabilization Dam foundation test anchors

Penalty Functions and Soft Constraints in RISKOptimizer

An illustration of penalty functions and how they can be used in soft constraints.

System Reliability 4-Model Series

A set of basic @RISK models for finding the system's reliability: 1. The probability that systems functions. 2. A version where the parts are correlated within and across modules. 3. A version that determines the numbers of parts required for the most cost-effective system. 4. A model for ...

Scheduling Classes with Uncertainty

An optimization model that schedules college classes with uncertain enrollments in different time slots.

Optimal Timing of Projects

The purpose of this model is to schedule starting years of 10 projects. Each project has a random expenditure in its initial year, a random revenue in the following year, and then a stream of annual revenues. The annual revenues for any project remain constant for a given number of years and ...

Workforce Planning 2-Model Series

Two versions of a workforce planning model are shown here: 1. A basic @RISK model for simulating several years of job movements within an organization. 2. A version that determines the "best" promotion/hiring parameters for a long-term outcome.

Best Route for a Traveling Salesperson 2-Model Series

Here, you can find an optimization model that determines the best route for a traveling salesperson with uncertain route costs. Additionally, there is a variation of this model where there are precedence constraints on the order of towns visited.

Scheduling Jobs with Due Dates

An optimization model for ordering jobs to meet due dates as nearly as possible.

Scheduling Job Tasks on Machines with Uncertainty

An optimization model that determines the best schedule for performing tasks on various machines.

Ordering Style Goods

A single-season optimization model for ordering style goods, where ordering can occur after early sales have been observed.

Newsvendor Model with Multiple Products

An optimization model for determining the best order quantities when substitute products are competing for total demand.

Multi-Product Inventory Production

A large optimization model for producing multiple SKUs to meet demand (based on a real Palisade case).

Hotel Booking 5-Model Series

Booking hotel rooms is an important problem for hotel managers. On the one hand, they want rooms to be occupied, and because of this and cancellations, they often overbook, that is, they take more reservations than the available number of rooms. On the other hand, they don't want to overbook ...

Airline Revenue Management

A model for determining optimal discount and full-fare limits on an airline flight.

Worker Scheduling

A company is open from 7AM until 11PM each day of the week. Each of its workers must work 5 consecutive days, and each day worked, he/she must work 4 consecutive hours, then have an hour off, and then work 4 more consecutive hours. The model assumes that the hourly schedule for a given worker ...

Comparison of Ordering Policies

A company faces infrequent and uncertain demands for a high-priced product. The company orders the product from a supplier, and there is an uncertain lead time from when an order is placed until it arrives. The company wants an ordering policy that keeps average inventory low but also keeps ...

Oil Output Smoothing

This model, based on a real consulting experience, is of an oil company that has leased a field with 10 old wells to be worked over and 15 new wells yet to be developed. It uses a standard model of exponential decline for annual outputs from the wells. The goal is to find a production schedule ...

When to Lower the Price

This model illustrates why companies lower their prices from time to time, that is, why they have sales. Essentially, it is because different customers have different reservation prices, the most they are willing to pay for a product they want. By reducing the price at key times, companies are ...

Web and Retail Pricing

This model illustrates pricing in a two-channel market, Web and retail. If the price in one channel is set low, it will not only create a higher demand in that channel, but it will tend to cannibalize demand from the other channel. So the pricing decisions are not obvious. RISKOptimizer is ...

Allocating Marketing Expenses to Retention and Acquisition

The goal of this model is to determine the allocation of marketing expenses to retaining current customers and acquiring new prospects. It assumes a nonlinear cost effectiveness functions for the percent obtained (either customers retained or prospects acquired), based on the amount spent per ...

Advertising in Different Media

This model finds the optimal numbers of ads for a company to place in various media to minimize the mean cost per exposure. There are two sources of uncertainty for each media: the total audience reached and the percentage of this audience that is the target for the company.

Work Allocation to Products

This model finds optimal allocations of work hours in several work centers toward production of several SKUs in a specific month. There are four sources of uncertainty: monthly demands for the SKUs, available work hours per day at the work centers, productivities of the work centers for each ...

Supply Chain Disruptions

This model illustrates how disruptions at suppliers, such as weather, strikes, or others, can affect a supply chain, and how such disruptions can be mitigated. The model has two suppliers and two manufacturers. Normally, each supplier supplies a single manufacturer. However, there are ...

Managing Supplier Inventory, Production

This is a supply chain model of the relationship between a manufacturer and its supplier, modeled from the point of view of the supplier. The manufacturer produces several products with random daily demands. These products require several components from the supplier. The supplier produces ...

Line Balancing

This is a simplified model of a multistage manufacturing process. Each stage has a number of identical machines, and each machine can produce a random number of items in a fixed period of time. Each stage feeds the next stage. However, any stage from stage 2 on can produce only as many items ...

Capacity Decision with Time Series

A manufacturing company that is building a new production facility for the next 15 years must decide how much capacity to build now in the face of future demand uncertainty, where demand in excess of capacity is lost. Future demands are forecast by using @RISK's Time Series Fit tool on ...

Aggregate Planning

This model plans production over the next six months in the face of uncertain demand. The company produces three products, and these products compete for labor hours. Each month there are 800 regular-time hours available, and up to 150 overtime hours can be used. The hours used must then be ...

Cash Management

A multi-day model for determining when cash should be invested or cash should be obtained.

Capital Budgeting

A capital budgeting model with uncertainty about projects' resource and capital usage and their NPVs.

Product Mix with Uncertainty 2-Model Series

This is a standard product mix model, where five product models must be assembled and then tested on either line 1 or line 2. You will find two versions of this model. 1. A product mix optimization model with uncertainty only in product demands. 2. A model that illustrates the real option of ...

Portfolio Optimization with Time Series

A portfolio optimization model that applies the Time Series Fit feature to historical stock price data.

Portfolio Balancing with Uncertainty

An optimization model that balances groups of securities in a portfolio.

Planning House Purchase

An optimization model for determining how to invest over a time horizon to accumulate a down payment for a house.

Planning for Retirement

An optimization model for deciding how to invest over a multi-year horizon to achieve a retirement goal.

E-Commerce Service 6-Model Series

A set of @RISK example models for E-Commerce Service. 1. A deterministic model to get started. 2. A basic @RISK model with demand uncertainty. 3. A version with demand uncertainty and uncertainty in price and cost. 4. A version that illustrates the RiskSimtable function for different values of ...

Accepting House Offers

An optimization model for deciding which of sequential house offers to accept.

Newsvendor Model with Demand Diversion

This model illustrates the newsvendor ordering model in a multiple-product setting with the possibility of demand diversion. This means that if supply of product A, say, is not sufficient to satisfy demand for product A, some customers (but not all of them) who wanted product A but couldn't ...

Conditional Value at Risk 2-Model Series

Two examples files to illustrate the "conditional value at risk" concept from finance. 1. A model to illustrate how to find the VaR and the CVaR for a portfolio of correlated investments. 2. A new version of the model above using RISKOptimizer to maximize the CVaR by choosing the portfolio ...

Capital Budgeting with Financial Statements

This model illustrates a portfolio optimization model which uses detailed financial calculations on a number of project worksheets to obtain project NPVs and present values of project costs. The goal is to select the projects for the portfolio that maximize the mean portfolio NPV, but to ...

Automobile Plant Expansion

A manufacturer of fuel efficient cars believes that demand for this type of cars might increase in the next few years, so it wants to expand its capacity. To finance this, the company plans to divert profits from car sales to a fund for eventual expansion. The model uses RISKOptimizer to find ...

Gold Mine Optimization

A gold mining project is divided into five separate mines, each with unique geological characteristics and cost variables. These variables (input costs, declination rates, plateau length, etc.) are all uncertain, and the price of gold is also uncertain. What is the optimal strategy for ...

Solar and Wind Power 2-Model Series

Two versions of a model which illustrates the daily output of a combination of solar and wind energy units. 1. The @RISK outputs include hourly and total daily output values for solar, wind, and combined solar and wind. 2. Extends the model above to use RISKOptimizer to find the best ...

Oil Drilling Decision Tree 5-Model Series

This oil drilling example is a classic decision tree problem, it demonstrates the use of PrecisionTree to analyze a multi-stage decision process. Our first decision is whether to run geological tests on the prospective site. Then, depending on the test results, the next decision is whether to ...

Spam Classification with Variable Impact Analysis

This model uses NeuralTools to classify a large number of email messages as spam or not spam, based on a large number of characteristics of the messages. It also uses the Variable Impact tool in NeuralTools to screen for predictors that might not be useful.

Chess Knight Moves

This model uses Evolver to check whether a chess knight can make 64 consecutive moves and hit each square exactly once. It doesn't optimize anything. It only tries to find a solution with the desired characteristic.

Optimal Advertising

This example illustrates two uses of Evolver. In the Parameter Estimation sheet, historical monthly values of sales and advertising are used to estimate the parameters of a sales function. Evolver is used to find the parameters that minimize the sum of squared errors between actual and ...

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