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This work fills a gap in the literature by providing an important link between Maple and its successful use in solving problems in Operations Research (OR). The numerical and graphical aspects of Maple make this software package an ideal tool for treating certain OR problems, and providing descriptive and optimisation-based analyses of deterministic and stochastic models. Detailed is Maple's treatment of some of the mathematical techniques used in OR modelling: e.g. algebra and calculus, ordinary and partial differential equators, linear algebra, transform methods and probability theory. A number of examples of OR techniques are presented, such as linear and non-linear programming, dynamic programming and optimal control, and stochastic processes. Almost every Maple statement used in the solution of a problem is clearly explained. At the same time, technical background material is presented in a rigorous mathematical manner to reach the OR novice and professional. A good bibliography at the end of each chapter and overall index at the end of the book are also included, and all Maple worksheets are downloadable from the author's website. This book should be of interest to graduate students in operations research, management science departments of business schools, industrial and systems engineering, economics, and mathematics. researchers and practitioners can use the Maple package to solve realistic OR-type problems that would be difficult or impossible to solve with other software packages.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This work fills an important gap in the literature by providing an important link between MAPLE and its successful use in solving problems in Operations Research (OR). The symbolic, numerical, and graphical aspects of MAPLE make this software package an ideal tool for treating certain OR problems and providing descriptive and optimization-based analyses of deterministic and stochastic models. Detailed is MAPLE's treatment of some of the mathematical techniques used in OR modeling: e.g., algebra and calculus, ordinary and partial differential equations, linear algebra, transform methods, and probability theory. A number of examples of OR techniques and applications are presented, such as linear and nonlinear programming, dynamic programming, stochastic processes, inventory models, queueing systems, and simulation. Throughout the text MAPLE statements used in the solutions of problems are clearly explained. At the same time, technical background material is presented in a rigorous mathematical manner to reach the OR novice and professional. Numerous end-of- chapter exercises, a good bibliography and overall index at the end of the book are also included, as well as MAPLE worksheets that are easily downloadable from the author's website at www.business.mcmaster.ca/msis/profs/parlar, or from the Birkhauser website at www.birkhauser.com/cgi-win/ISBN/0-8176-4165-3. The book is intended for advanced undergraduate and graduate students in operations research, management science departments of business schools, industrial and systems engineering, economics, and mathematics. As a self-study resource, the text can be used by researchers and practitioners who want a quick overview of MAPLE's usefulness in solving realistic OR problems that would be difficult or impossible to solve with other software packages.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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