„Dr. Phillips has used other texts, but he is especiallyenthused with this book, influenced by student feedback. He says,“Algorithmic ideas are introduced at a pace that emphasizesand encourages intuitive understanding.„ (InformsJournal on Computing, 1 June 2012)
“The book is aimed at serving upper-undergraduate and graduatestudents of all fields as a comprehensive textbook or as areference for studies on the subject.„ (Zentralblatt MATH,2011)
“The result is a clear-cut resource for understanding threecornerstones of deterministic operations research: modelingreal-world problems as linear optimization problems; designing thenecessary algorithms to solve these problems; and usingmathematical theory to justify algorithmic development." (InfoTECHSpotlight - TMCnet, 8 February 2011)
Uniquely blends mathematical theory and algorithm design forunderstanding and modeling real-world problems
Optimization modeling and algorithms are key components toproblem-solving across various fields of research, from operationsresearch and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design ofsolution methods for both continuous and discrete linearoptimization problems. The result is a clear-cut resource forunderstanding three cornerstones of deterministic operationsresearch: modeling real-world problems as linear optimizationproblem; designing the necessary algorithms to solve theseproblems; and using mathematical theory to justify algorithmicdevelopment.
Treating real-world examples as mathematical problems, theauthor begins with an introduction to operations research andoptimization modeling that includes applications form sportsscheduling an the airline industry. Subsequent chapters discussalgorithm design for continuous linear optimization problems, covering topics such as convexity. Farkas' Lemma, and thestudy of polyhedral before culminating in a discussion of theSimplex Method. The book also addresses linear programming dualitytheory and its use in algorithm design as well as the Dual SimplexMethod. Dantzig-Wolfe decomposition, and a primal-dual interiorpoint algorithm. The final chapters present network optimizationand integer programming problems, highlighting various specializedtopics including label-correcting algorithms for the shortest pathproblem, preprocessing and probing in integer programming, liftingof valid inequalities, and branch and cut algorithms.
Concepts and approaches are introduced by outlining examplesthat demonstrate and motivate theoretical concepts. The accessiblepresentation of advanced ideas makes core aspects easy tounderstand and encourages readers to understand how to think aboutthe problem, not just what to think. Relevant historical summariescan be found throughout the book, and each chapter is designed asthe continuation of the „story“ of how to both modeland solve optimization problems by using the specificproblems-linear and integer programs-as guides. The book'svarious examples are accompanied by the appropriate models andcalculations, and a related Web site features these models alongwith Maple(TM) and MATLAB® content for the discussedcalculations.
Thoroughly class-tested to ensure a straightforward, hands-onapproach, Deterministic Operations Research is an excellentbook for operations research of linear optimization courses at theupper-undergraduate and graduate levels. It also serves as aninsightful reference for individuals working in the fields ofmathematics, engineering, computer science, and operations researchwho use and design algorithms to solve problem in their everydaywork.
Optimization modeling and algorithms are key components toproblem-solving across various fields of research, from operationsresearch and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design ofsolution methods for both continuous and discrete linearoptimization problems. The result is a clear-cut resource forunderstanding three cornerstones of deterministic operationsresearch: modeling real-world problems as linear optimizationproblem; designing the necessary algorithms to solve theseproblems; and using mathematical theory to justify algorithmicdevelopment.
Treating real-world examples as mathematical problems, theauthor begins with an introduction to operations research andoptimization modeling that includes applications form sportsscheduling an the airline industry. Subsequent chapters discussalgorithm design for continuous linear optimization problems, covering topics such as convexity. Farkas' Lemma, and thestudy of polyhedral before culminating in a discussion of theSimplex Method. The book also addresses linear programming dualitytheory and its use in algorithm design as well as the Dual SimplexMethod. Dantzig-Wolfe decomposition, and a primal-dual interiorpoint algorithm. The final chapters present network optimizationand integer programming problems, highlighting various specializedtopics including label-correcting algorithms for the shortest pathproblem, preprocessing and probing in integer programming, liftingof valid inequalities, and branch and cut algorithms.
Concepts and approaches are introduced by outlining examplesthat demonstrate and motivate theoretical concepts. The accessiblepresentation of advanced ideas makes core aspects easy tounderstand and encourages readers to understand how to think aboutthe problem, not just what to think. Relevant historical summariescan be found throughout the book, and each chapter is designed asthe continuation of the „story“ of how to both modeland solve optimization problems by using the specificproblems-linear and integer programs-as guides. The book'svarious examples are accompanied by the appropriate models andcalculations, and a related Web site features these models alongwith Maple(TM) and MATLAB® content for the discussedcalculations.
Thoroughly class-tested to ensure a straightforward, hands-onapproach, Deterministic Operations Research is an excellentbook for operations research of linear optimization courses at theupper-undergraduate and graduate levels. It also serves as aninsightful reference for individuals working in the fields ofmathematics, engineering, computer science, and operations researchwho use and design algorithms to solve problem in their everydaywork.
