In today's competitive global economy, people are faced with many difficult decisions. Such decisions may involve thousands or millions of potential alternatives. A model can provide valuable assistance in analyzing decisions and finding good solutions. 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 OptQuest optimization model has four major elements: an objective, optional requirements, Crystal Ball decision variables, and optional constraints.
Optimization Objectives—Elements that represents the target goal of the optimization, such as maximizing profit or minimizing cost, based on a forecast and related decision variables.
Requirements—Optional restrictions placed on forecast statistics. All requirements must be satisfied before a solution can be considered feasible.
Decision Variables—Variables over which you have control; for example, the amount of product to make, the number of dollars to allocate among different investments, or which projects to select from among a limited set.
Constraints—Optional restrictions placed on decision variable values. For example, a constraint may ensure that the total amount of money allocated among various investments cannot exceed a specified amount, or at most one project from a certain group can be selected.
For direct experience in setting up a model and running an optimization, see Tutorial 2 — Portfolio Allocation Model .