Decision
Making Under Uncertainty with RISKOptimizer: A Training CD
Working with RISKOptimizer is as easy as working with @RISK, Evolver, or any other
DecisionTools programme. You can break it down into five steps:
Step 1: Build Your Spreadsheet Model
Build a model in Microsoft Excel or start with any spreadsheet that you have already
built. Use macros, lookup tables, whatever you need to make your model complete.
You can even use pre-existing @RISK models! (See next step.)
 |
Step 2: Define Uncertainty
Replace uncertain values in your model with probability distribution functions that
represent a range of possible values. If you're an @RISK user, this part will sound
familiar. In fact, RISKOptimizer uses @RISK functions to represent uncertainty. Use
any of @RISK's 38 distribution functions in your model.
Step 3: Set Up the Optimisation Problem
This part will be familiar to Evolver users. Setting up the optimisation involves choosing
the cell to be maximised or minimised, specifying the cells whose values RISKOptimizer
can adjust during an optimisation, and specifying constraints. For example, you may
wish to maximise profits by varying the number of different products you produce, making
sure you don't produce more products than you have raw materials for.
Things are a little different with RISKOptimizer when compared to a traditional optimiser
like Solver or Evolver. Instead of choosing a cell to maximise or minimise, you'll
be choosing a statistic of that cell. Since RISKOptimizer will be running simulations,
it doesn't make much sense to try and maximise the value of a cell whose value changes
with every iteration! Instead, you'll want to maximise the mean of the distribution
generated in the cell during each simulation, or minimise the standard deviation, or
maximise the 95th percentile.
 |
RISKOptimizer's intuitive dialogue boxes make setting things up easy. You can specify
constraints -- either to be evaluated each iteration of a trial solution's simulation
(such as A100<2000) or at the end of a trial solution's simulation (such as the
StdDev of C15<100). As in Evolver, constraints can be either hard (they must be
met) or soft (the result is penalised when they are not met).
You can also specify the stopping conditions for the optimisation as well as for each
trial/simulation. For example, you can let the whole optimisation run ten minutes,
running 1000 iterations per simulation. RISKOptimizer can also use convergence monitoring
to automatically determine how long to run each simulation - so you don't run too few
or too many iterations.
RISKOptimizer's advanced projected convergence feature can determine stable results
based on previous trials/simulations. Convergence monitoring makes RISKOptimizer fast
and very efficient!
Step 4: Running an Optimisation
Running an optimisation in RISKOptimizer is similar to running one in Evolver. RISKOptimizer
generates a number of trials and uses Genetic Algorithms to continually improve results
of each trial. However, each trial is a simulation and the result for the trial is
the statistic that you wish to minimise or maximise for the distribution of the target
cell (mean, standard deviation, etc.). For each new trial solution, another simulation
is run and another value for the target statistic is generated. The result is the trial
solution that provides the best answer to your problem!
RISKOptimizer reports on your optimisation with details on the best simulation run
or even all simulations run. You'll see the values for all your adjustable inputs,
the status of your constraints and statistics on the distribution for your objective.
Step 5: Want More on Your Best Simulation?
Simply run your model with the best values for your inputs (as identified by RISKOptimizer),
through @RISK -- no changes required! You'll get all the graphs and reports you expect
from @RISK, detailing your optimal simulation. The link between the two products couldn't
be easier!
Product Versions
RISKOptimizer has a limit of 80 adjustable cells, with unlimited probability
distributions. RISKOptimizer Industrial features unlimited adjustable
cells and unlimited probability distributions.
Read More!
RISKOptimizer
Main Page
Excerpt
from Decision Making Under Uncertainty with RISKOptimizer:
Use RISKOptimizer with Product
Mix Decisions
Fly
RISKOptimizer to Profit Maximisation: A typical optimisation
problem that benefits from
RISKOptimizer's combination of optimisation and simulation.
Review: RISKOptimizer:
Powerful Tool Eliminates Much of the "Guesswork" Inherent to
Model Derivation
Book: Financial
Models Using Simulation and Optimization
Book: Decision
Making Under Uncertainty with RISKOptimizer
가격에는
부가세를 제외한 1년간의 Maintenance를
비롯한 모든 제반 비용이 포함되어 있습니다. 필요하시면 반품
및 환불에 관한 규정 과 배송
방법 및 기간 를 참고 바랍니다.
|
||||||||||||
RISKOptimizer System Requirements
Minimum
Platform: IBM PC compatible Pentium-equivalent or higher, 16MB RAM, Windows
98, NT 4.0, Windows 2000, Windows XP
Recommended: 32
MB RAM, or greater
Spreadsheet: Windows
Excel 97 or higher
Version: 1.0
Developer's
Kit : RISKOptimizer Developer's Kit
Technical
Support: 30 days free. Further support available through Maintenance
Plan.
Demo: Web
download and free demo CD with trial
version available.
Training: Available
through Palisade's Software Training Courses.
Recommended
Books: Decision Making Under Uncertainty
with RISKOptimizer; Financial Models
Using Simulation and Optimization; Financial
Models Using Simulation and Optimization II; RISKOptimizer
for Business Applications; Trends
and Tools in Operations Management