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Introduction to the Mathematics of Operations Research with Mathematica®

List Price: $94.99
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9780367390785
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  • Product Details

    Author:
    Kevin J. Hastings
    Format:
    Paperback
    Pages:
    588
    Publisher:
    CRC Press (September 19, 2019)
    Language:
    English
    ISBN-13:
    9780367390785
    Weight:
    27.25oz
    Dimensions:
    6" x 9"
    File:
    TAYLORFRANCIS-TayFran_260716044336477-20260716.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $94.99
    Case Pack:
    10
    As low as:
    $90.24
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Audience:
    Professional and scholarly
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Chapman and Hall/CRC
  • Overview

    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.