This book considers the problem of determining how many barrels of crude oil an oil-producing and exporting country should produce annually for export along with several other important problems that decision-makers in the crude oil industry face and discusses procedures for finding optimum solutions for them. It considers the important Objective Functions they need in making these critical decisions, and discusses procedures to find the best solutions. Outputs from the treatment units, in an oil refinery are only semi-finished products; these are blended into finished products like gasoline, diesel oil, etc., meeting various specifications that the marketplace demands. The book discusses models for solving these problems optimally with examples.

This textbook is comprised of detailed case studies covering challenging real world applications of OR techniques. Among the overall goals of the book is to provide readers with descriptions of the history and other background information on a variety of industries, service or other organizations in which decision making is an important component of their daily operations. The book considers all methods of optimum decision making in order to improve performances. It also compares possible solutions obtained by different approaches, concluding with a recommendation of the best among them for implementation. By exposing students to a variety of applications in a variety of areas and explaining how they can be modeled and solved, the book helps students develop the skills needed for modeling and solving problems that they may face in the workplace. Each chapter of "Case Studies in Operations Research: Applications of Optimal Decision Making" also includes additional data provided on the book's website on Springer.com. These files contain a brief description of the area of application, the problem and the required outputs. Also provided are links to access all the data in the problem. Finally there are project exercises for students to practice what they have learnt in the chapter, which can also be used by instructors as project assignments in their courses.

Linear programming (LP), modeling, and optimization are very much the fundamentals of OR, and no academic program is complete without them. No matter how highly developed one 's LP skills are, however, if a fine appreciation for modeling isn t developed to make the best use of those skills, then the truly best solutions are often not realized, and efforts go wasted.

Katta Murty studied LP with George Dantzig, the father of linear programming, and has written the graduate-level solution to that problem. While maintaining the rigorous LP instruction required, Murty's new book is unique in his focus on developing modeling skills to support valid decision making for complex real world problems. He describes the approach as 'intelligent modeling and decision making' to emphasize the importance of employing the best expression of actual problems and then applying the most computationally effective and efficient solution technique for that model.

This book considers the problem of determining how many barrels of crude oil an oil-producing and exporting country should produce annually for export along with several other important problems that decision-makers in the crude oil industry face and discusses procedures for finding optimum solutions for them. It considers the important Objective Functions they need in making these critical decisions, and discusses procedures to find the best solutions. Outputs from the treatment units, in an oil refinery are only semi-finished products; these are blended into finished products like gasoline, diesel oil, etc., meeting various specifications that the marketplace demands. The book discusses models for solving these problems optimally with examples.

This textbook is comprised of detailed case studies covering challenging real world applications of OR techniques. Among the overall goals of the book is to provide readers with descriptions of the history and other background information on a variety of industries, service or other organizations in which decision making is an important component of their daily operations. The book considers all methods of optimum decision making in order to improve performances. It also compares possible solutions obtained by different approaches, concluding with a recommendation of the best among them for implementation. By exposing students to a variety of applications in a variety of areas and explaining how they can be modeled and solved, the book helps students develop the skills needed for modeling and solving problems that they may face in the workplace. Each chapter of "Case Studies in Operations Research: Applications of Optimal Decision Making" also includes additional data provided on the book's website on Springer.com. These files contain a brief description of the area of application, the problem and the required outputs. Also provided are links to access all the data in the problem. Finally there are project exercises for students to practice what they have learnt in the chapter, which can also be used by instructors as project assignments in their courses.

Linear programming (LP), modeling, and optimization are very much the fundamentals of OR, and no academic program is complete without them. No matter how highly developed one s LP skills are, however, if a fine appreciation for modeling isn t developed to make the best use of those skills, then the truly best solutions are often not realized, and efforts go wasted.

Katta Murty studied LP with George Dantzig, the father of linear programming, and has written the graduate-level solution to that problem. While maintaining the rigorous LP instruction required, Murty's new book is unique in his focus on developing modeling skills to support valid decision making for complex real world problems. He describes the approach as 'intelligent modeling and decision making' to emphasize the importance of employing the best expression of actual problems and then applying the most computationally effective and efficient solution technique for that model."