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Introduction to the Mathematics of Operations Research with Mathematica®
Introduction to the Mathematics of Operations Research with Mathematica®
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★★★★★
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€223.20
A01=Kevin J. Hastings
Adjacency Matrix
advanced operations research techniques
Author_Kevin J. Hastings
Basic Feasible Solution
Bipartite Graph
Brownian motions
Category=PBW
Connected Component
Constraint Coefficients
Directed Graph
dynamic optimization
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Final Tableau
graph theory
Initial Tableau
LP Problem
Markov Chain
Markov chains
mathematical simulation
Maximal Flow Algorithm
network flow analysis
Non-basic Variables
Objective Row
operations research
Poisson processes
probability theory
Profit Coefficient
quantitative decision methods
Recurrence Class
Simplex Algorithm
Simplex Tableau
Slack Variable
Spanning Tree
Spanning Tree Algorithm
stochastic modeling
Transition Diagram
Transition Matrix
Undeclared Variables
Undirected Graph
Vertex Labeling
Product details
- ISBN 9781574446128
- Weight: 975g
- Dimensions: 152 x 229mm
- Publication Date: 30 May 2006
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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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.
Hastings, Kevin J.
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