This is a book about optimization with an emphasis on building models and using spreadsheets. Each facet of this themeāmodels, spreadsheets, and optimizationāhas a role in defining the emphasis of our coverage.
A model is a simplified representation of a situation or problem. Models attempt to capture the essential features of a complicated situation so that it can be studied and understood more completely. In the worlds of business, engineering, and science, models aim to improve our understanding of practical situations. Models can be built with tangible materials, or words, or mathematical symbols and expressions. A mathematical model is a model that is constructedāand also analyzedāusing mathematics. In this book, we focus on mathematical models. Moreover, we work with decision models, or models that contain representations of decisions. The term also refers to models that support decision-making activities.
A spreadsheet is a row-and-column layout of text, numerical data, and logical information. The spreadsheet version of a model contains the modelās elements, linked together by specific logical information. Electronic spreadsheets, like those built using MicrosoftĀ® Office ExcelĀ®, have become familiar tools in the business, engineering, and scientific worlds. Spreadsheets are relatively easy to understand, and people often rely on spreadsheets to communicate their analyses. In this book, we focus on the use of spreadsheets to represent and analyze mathematical models.
This text is written for an audience that already has some familiarity with Excel. Our coverage assumes a level of facility with Excel comparable to a beginnerās level. Someone who has used other peopleās spreadsheets and built simple spreadsheets for some purposeāeither personal or organizationalāhas probably developed this skill level. Box 1.1 describes the Excel skill level assumed. Readers without this level of background are encouraged to first work through some introductory materials, such as the books by McFedries (1) and Walkenbach (2).
BOX 1.1 Excel Skills Assumed as Background for This Book
Navigating in workbooks, worksheets, and windows
Using the cursor to select cells, rows, columns, and noncontiguous cell ranges
Entering text and data; copying and pasting; filling down or across
Formatting cells (number display, alignment, font, border, and protection)
Editing cells (using the formula bar and cell edit capability [F2])
Entering formulas and using the function wizard
Using relative and absolute addresses
Using range names
Creating charts and graphs
Optimization is the process of finding the best values of the variables for a particular criterion or, in our context, the best decisions for a particular measure of performance. The elements of an optimization problem are a set of decisions, a criterion, and perhaps a set of required conditions, or constraints, that the decisions must satisfy. These elements lend themselves to description in a mathematical model. The term optimization sometimes refers specifically to a procedure that is implemented by software. However, in this book, we expand that perspective to include the model-building process as well as the process of finding the best decisions.
Not all mathematical models are optimization models. Some models merely describe the logical relationship between inputs and outputs. Optimization models are a special kind of model in which the purpose is to find the best value of a particular output measure and the choices that produce it. Optimization problems abound in the real world, and if weāre at all ambitious or curious, we often find ourselves seeking solutions to those problems. Business firms are very interested in optimization because making good decisions helps a firm run efficiently, perform profitably, and compete effectively. In this book, we focus on optimization problems expressed in the form of spreadsheet models and solved using a spreadsheet-based approach.
1.1 ELEMENTS OF A MODEL
To restate our premise, we are interested in mathematical models. Specifically, we are interested in two formsāalgebraic and spreadsheet models. In the former, we use algebraic notation to represent elements and relationships, and in the latter, we use spreadsheet entries and structure. For example, in an algebraic statement, we might use the variable x to represent a quantitative decision, and we might use some function f(x) to represent the measure of performance that results from choosing decision x. Then, we might adopt the letter z to represent a criterion for decision making and construct the equation z = f(x) to guide the choice of a decision. Algebra is the basic language of analysis largely because it is precise and compact.
As an introductory modeling example, letās consider the price decision in the scenario of Example 1.1.
EXAMPLE 1.1 Price, Demand, and Profit
Our firmās production department has carried out a cost accounting study and found that the unit cost for one of its main products is $40. Meanwhile, the marketing department has estimated the relationship between price and sales volume (the so-called d...