Description

Book Synopsis


Table of Contents
PART 1 The Essence of Management Science and Business Analytics
1 Introduction
2 Overview of the Analysis Process

PART 2 Models for Predictive Analytics
3 Classification and Prediction Models for Predictive Analytics
4 Predictive Analytics Based on Traditional Forecasting Methods

PART 3 Using Linear Programming to Perform Prescriptive Analytics
5 Linear Programming: Basic Concepts
6 Linear Programming: Formulation and Applications
7 The Art of Modeling with Spreadsheets
8 What-If Analysis for Linear Programming
9 Network Optimization Problems

PART 4 Using Integer or Nonlinear Programming to Perform Prescriptive Analytics
10 Integer Programming
11 Nonlinear Programming

PART 5 Traditional Uncertainty Models for Performing Predictive or Prescriptive Analytics
12 Decision Analysis
13 Queueing Models
14 Computer Simulation: Basic Concepts
15 Computer Simulation with Analytic Solver

APPENDIXES
A Tips for Using Microsoft Excel for Modeling
B Partial Answers to Selected Problems

Introduction to Management Science ISE

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    A Paperback / softback by Frederick Hillier, Mark Hillier

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      Publisher: McGraw-Hill Education
      Publication Date: Publication Date: 15/11/2022
      ISBN13: 9781265040055, 978-1265040055
      ISBN10: 1265040052
      Also in:
      Business, Finance & Law Business and Management

      Description

      Book Synopsis


      Table of Contents
      PART 1 The Essence of Management Science and Business Analytics
      1 Introduction
      2 Overview of the Analysis Process

      PART 2 Models for Predictive Analytics
      3 Classification and Prediction Models for Predictive Analytics
      4 Predictive Analytics Based on Traditional Forecasting Methods

      PART 3 Using Linear Programming to Perform Prescriptive Analytics
      5 Linear Programming: Basic Concepts
      6 Linear Programming: Formulation and Applications
      7 The Art of Modeling with Spreadsheets
      8 What-If Analysis for Linear Programming
      9 Network Optimization Problems

      PART 4 Using Integer or Nonlinear Programming to Perform Prescriptive Analytics
      10 Integer Programming
      11 Nonlinear Programming

      PART 5 Traditional Uncertainty Models for Performing Predictive or Prescriptive Analytics
      12 Decision Analysis
      13 Queueing Models
      14 Computer Simulation: Basic Concepts
      15 Computer Simulation with Analytic Solver

      APPENDIXES
      A Tips for Using Microsoft Excel for Modeling
      B Partial Answers to Selected Problems

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