Rockwell Automation Arena OptQuest Users Guide - Manual (Page 23)

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Understanding the Terminology
This chapter includes a description of the three major elements of an optimization model:
controls, constraints, and the objective. Coverage is also given on the different types of
optimization models and how OptQuest deals with them.
What is an optimization model?
In today’s highly competitive global environment, people are faced with many difficult
decisions; such decisions include allocating financial resources, building or expanding
facilities, managing inventories, and determining product-mix strategies. At the same
time, such decisions might involve thousands or millions of potential alternatives.
Considering and evaluating each of them would be impractical or even impossible in most
settings. A simulation model—a representation of a problem or system—can provide
valuable assistance in analyzing designs and finding good solutions. Simulation models
capture the most important features of a problem and present them in a form that is easy to
interpret. Models often provide insights that intuition alone cannot. An optimization
model—a model that seeks to maximize or minimize some quantity, such as profit or
cost—has three major elements: controls, constraints, and an objective.
Controls Are either Arena Variables or Resources that can be meaningfully
manipulated to affect the performance of a simulated system; for example,
the amount of product to make, the number of workers to assign to an
activity, or the fleet size in a transportation system.
Constraints Are relationships among controls and/or responses. For example, a constraint
might ensure that the total amount of money allocated among various
investments cannot exceed a specified amount, or at most, one machine from
a certain group can be selected.
Objective Is a mathematical response or an expression used to represent the model's
objective, such as minimizing queues or maximizing profits, in terms of
statistics collected in the Arena model.