The OptQuest add-on adds full optimization functionality to Enterprise Dynamics. With this optimizer you can optimize simulation models to determine an optimal configuration e.g. to maximize output or minimize costs. OptQuest is a product from OptTek. It provides user-friendly software to customers who may have limited knowledge of how optimization works yet who need access to the sophisticated optimization techniques developed by Dr. Glover. The state-of-the-art optimization technology embedded in OptQuest can be used directly by analysts to search for optimal solutions to complex business and engineering problems. Models using the optimization objects can communicate with OptQuest Engine via a flexible and intuitive object model. OptQuest Engine uses metaheuristic, mathematical optimization, and neural network components to guide the search for best solutions to decision and planning problems of all types. The objects tell OptQuest Engine the quality of each solution generated during the search, by calling an evaluator (such as an objective function) that can take any form. For example, the evaluator may simulate a complex system to determine its behavior based on a proposed solution.

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. Such decisions might involve thousands or millions of potential alternatives. Considering and evaluating each of them would be impractical or even impossible. 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 optimization model has three major elements: decision variables, constraints, and an objective.

Add optimization technology to ED

Decision variables are quantities 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 describe relationships among decision variables that restrict the values of the decision variables. 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 project from a certain group can be selected.

An objective gives a mathematical representation of the model's objective, such as maximizing profit or minimizing cost, in terms of the decision variables. The solution to an optimization model provides a set of values for the decision variables that optimizes (maximizes or minimizes) the associated objective. OptQuest assumes that the relationships among decision variables are such that they cannot be modeled with simple linear or nonlinear equations. Therefore the value of the objective function is found by executing an Enterprise Dynamics simulation. Additional output from simulation runs can be used to model requirements.

Requirements are variables that are part of the output of the simulation for which upper and/or lower bounds can be defined. OptQuest searches for solutions that meet the specified constraints (i.e., constraint feasible) and also meet the specified requirements (i.e., requirement-feasible).