THE RISE OF ANALYTICS TOGETHER WITH OPERATIONS RESEARCH

By -

A very popular approach now is to use today’s premier spreadsheet package, Microsoft Excel, to formulate small OR models in a spreadsheet format. Included with standard Excel is an add-in, called Solver (a product of Frontline Systems, Inc.), that can be used to solve many of these models. Your OR Courseware includes separate Excel files for nearly every chapter in this book. Each time a chapter presents an example that can be solved using Excel, the complete spreadsheet formulation and solution is given in that chapter’s Excel files. For many of the models in the book, an Excel template also is pro- vided that already includes all the equations necessary to solve the model.

New with this edition of the textbook is a powerful software package from Frontline Systems called Analytic Solver Platform for Education (ASPE), which is fully compat- ible with Excel and Excel’s Solver. The recently released Analytic Solver Platform com- bines all the capabilities of three other popular products from Frontline Systems: (1) Premium Solver Platform (a powerful spreadsheet optimizer that includes five solvers for linear, mixed-integer, nonlinear, non-smooth, and global optimization), (2) Risk Solver Pro (for simulation and risk analysis), and (3) XLMiner (an Excel-based tool for data mining and forecasting). It also has the ability to solve optimization models involving uncertainty and recourse decisions, perform sensitivity analysis, and construct decision trees. It even has an ultra-high-performance linear mixed-integer optimizer. The student version of Analytic Solver Platform retains all these capabilities when dealing with smaller problems. Among the special features of ASPE that are highlighted in this book are a greatly enhanced ver- sion of the basic Solver included with Excel (as described in Sec. 3.5), the ability to build decision trees within Excel (as described in Sec. 16.5), and tools to build simulation mod- els within Excel (as described in Sec. 20.6).

After many years, LINDO (and its companion modeling language LINGO) continues to be a popular OR software package. Student versions of LINDO and LINGO now can be downloaded free from the Web at www.lindo.com. This student version also is provided in your OR Courseware. As for Excel, each time an example can be solved with this package, all the details are given in a LINGO/LINDO file for that chapter in your OR Courseware.

When dealing with large and challenging OR problems, it is common to also use a modeling system to efficiently formulate the mathematical model and enter it into the com- puter. MPL is a user-friendly modeling system that includes a considerable number of elite solvers for solving such problems very efficiently. These solvers include CPLEX, GUROBI, CoinMP, and SULUM for linear and integer programming (Chaps. 3-10 and 12), as well as CONOPT for convex programming (part of Chap. 13) and LGO for global opti- mization (Sec. 13.10), among others. A student version of MPL, along with the student version of its solvers, is available free by downloading it from the Web. For your conve- nience, we also have included this student version (including the six solvers just men- tioned) in your OR Courseware. Once again, all the examples that can be solved with this package are detailed in MPL/Solvers files for the corresponding chapters in your OR Courseware. Furthermore, academic users can apply to receive full-sized versions of MPL, CPLEX, and GUROBI by going to their respective websites.2 This means that any academic users (professors or students) now can obtain professional versions of MPL with CPLEX and GUROBI for use in their coursework.

We will further describe these four software packages and how to use them later (espe- cially near the end of Chaps. 3 and 4). Appendix 1 also provides documentation for the OR Courseware, including OR Tutor and IOR Tutorial.

To alert you to relevant material in OR Courseware, the end of each chapter from Chap. 3 onward has a list entitled Learning Aids for This Chapter on our Website. As

2MPL: http://www.maximalsoftware.com/academic; CPLEX: http://www-03.ibm.com/ibm/university/academic/pub/ page/ban_ilog_programming; GUROBI: http://www.gurobi.com/products/licensing-and-pricing/academic-licensing

explained at the beginning of the problem section for each of these chapters, symbols also are placed to the left of each problem number or part where any of this material (including demonstration examples and interactive procedures) can be helpful.

Another learning aid provided on our website is a set of Solved Examples for each chapter (from Chap. 3 onward). These complete examples supplement the examples in the book for your use as needed, but without interrupting the flow of the material on those many occasions when you don’t need to see an additional example. You also might find these supplementary examples helpful when preparing for an examination. We always will mention whenever a supplementary example on the current topic is included in the Solved Examples section of the book’s website. To make sure you don’t overlook this mention, we will boldface the words additional example (or something similar) each time.

The website also includes a glossary for each chapter.

Comments

Post a Comment

Popular posts from this blog

NETWORK OPTIMIZATION MODELS:THE MINIMUM SPANNING TREE PROBLEM

By -
Image
THE MINIMUM SPANNING TREE PROBLEM The minimum spanning tree problem bears some similarities to the main version of the shortest-path problem presented in the preceding section. In both cases, an undi r ecte d and connected network is being considered, where the given information includes some mea- sure of the positive length (distance, cost, time, etc.) associated with each link. Both problems also involve choosing a set of links that have the shortest total length among all sets of links that satisfy a certain property. For the shortest-path problem, this property is that the chosen links must provide a path between the origin and the destination. For the minimum spanning tree problem, the required property is that the chosen links must provide a path between ea c h pair of nodes. The minimum spanning tree problem can be summarized as follows: 1. You are given the nodes of a network but not the links. Instead, you are given the po- tential links and the positive length for each
Read more

DUALITY THEORY:THE ESSENCE OF DUALITY THEORY

By -
Image
THE ESSENCE OF DUALITY THEORY Given our standard form for the primal problem at the left (perhaps after conversion from another form), its dual problem has the form shown to the right. Thus, with the primal problem in maximizatio n form, the dual problem is in minimization form instead. Furthermore, the dual problem uses exactly the same pa r amete r s as the primal problem, but in different locations, as summarized below. 1. The coefficients in the objective function of the primal problem are the right-hand sides of the functional constraints in the dual problem. 2. The right-hand sides of the functional constraints in the primal problem are the coef- ficients in the objective function of the dual problem. 3. The coefficients of a variable in the functional constraints of the primal problem are the coefficients in a functional constraint of the dual problem. To highlight the comparison, now look at these same two problems in matrix notation (as introduced at the beginn
Read more

DECISION SUPPORT SYSTEMS:DIALOG GENERATION AND MANAGEMENT SYSTEMS

By -
Image
DIALOG GENERATION AND MANAGEMENT SYSTEMS In our efforts in this chapter, we envision a basic DSS structure of the form shown in Figure 12. This figure also shows many of the operational functions of the database management system (DBMS) and the model base management system (MBMS). The primary purpose of the dialog generation and management system (DGMS) is to enhance the propensity and ability of the system user to use and benefit from the DSS. There are doubtless few users of a DSS who use it because of necessity. Most uses of a DSS are optional, and the decision maker must have some motivation and desire to use a DSS or it will likely remain unused. DSS use can occur in a variety of ways. In all uses of a DGMS, it is the DGMS that the user interacts with. In an early seminal text, Bennett (1983) posed three questions to indicate this centrality: 1. What presentations is the user able to see at the DSS display terminal? 2. What must the user know about what is seen at the display
Read more