Introduction to the Mathematics of Operations Research with Mathematica®.

Hastings, Kevin J.:

ISBN 10: 1574446126 / ISBN 13: 9781574446128

Edité par Boca Raton, Chapman and Hall/CRC, 2018

A propos de cet article

589 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. 9781574446128 Sprache: Englisch Gewicht in Gramm: 990.

N° de réf. du vendeur 2340227

Détails bibliographiques

• Titre: Introduction to the Mathematics of Operations Research with Mathematica®.
• Éditeur: Boca Raton, Chapman and Hall/CRC
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 1574446126
• ISBN à 13 chiffres: 9781574446128
• Reliure: Couverture rigide
• Édition: 2nd ed.
• Poids: 990 grammes
• Catalogues du vendeur:
  • SA MATHEMATIK

A propos de ce titre

Synopsis

The breadth of information about operations research and the overwhelming size of previous sources on the subject make it a difficult topic for non-specialists to grasp. Fortunately, Introduction to the Mathematics of Operations Research with Mathematica®, Second Edition delivers a concise analysis that benefits professionals in operations research and related fields in statistics, management, applied mathematics, and finance.

The second edition retains the character of the earlier version, while incorporating developments in the sphere of operations research, technology, and mathematics pedagogy. Covering the topics crucial to applied mathematics, it examines graph theory, linear programming, stochastic processes, and dynamic programming. This self-contained text includes an accompanying electronic version and a package of useful commands. The electronic version is in the form of Mathematica notebooks, enabling you to devise, edit, and execute/reexecute commands, increasing your level of comprehension and problem-solving.

Mathematica sharpens the impact of this book by allowing you to conveniently carry out graph algorithms, experiment with large powers of adjacency matrices in order to check the path counting theorem and Markov chains, construct feasible regions of linear programming problems, and use the "dictionary" method to solve these problems. You can also create simulators for Markov chains, Poisson processes, and Brownian motions in Mathematica, increasing your understanding of the defining conditions of these processes. Among many other benefits, Mathematica also promotes recursive solutions for problems related to first passage times and absorption probabilities.

À propos de l?auteur

Hastings, Kevin J.