Book contents
- Frontmatter
- Contents
- Notation
- Preface
- Part I Overview of Optimization:Applications and Problem Formulations
- Part II From General Mathematical Background to General Nonlinear Programming Problems (NLP)
- Part III Formulation and Solution of Linear Programming (LP) Problems
- 10 Introduction to LP Models
- 11 Numerical Solution of LP Problems Using the Simplex Method
- 12 A Sampler of LP Problem Formulations
- 13 Regression Revisited: Using LP to Fit Linear Models
- 14 Network Flow Problems
- 15 LP and Sensitivity Analysis, in Brief
- 16 Multiobjective Optimization
- 17 Optimization under Uncertainty
- 18 Mixed-Integer Programming Problems
- 19 Global Optimization
- 20 Optimal Control Problems (Dynamic Optimization)
- 21 System Identification and Model Predictive Control
- Index
12 - A Sampler of LP Problem Formulations
from Part III - Formulation and Solution of Linear Programming (LP) Problems
Published online by Cambridge University Press: 17 December 2020
- Frontmatter
- Contents
- Notation
- Preface
- Part I Overview of Optimization:Applications and Problem Formulations
- Part II From General Mathematical Background to General Nonlinear Programming Problems (NLP)
- Part III Formulation and Solution of Linear Programming (LP) Problems
- 10 Introduction to LP Models
- 11 Numerical Solution of LP Problems Using the Simplex Method
- 12 A Sampler of LP Problem Formulations
- 13 Regression Revisited: Using LP to Fit Linear Models
- 14 Network Flow Problems
- 15 LP and Sensitivity Analysis, in Brief
- 16 Multiobjective Optimization
- 17 Optimization under Uncertainty
- 18 Mixed-Integer Programming Problems
- 19 Global Optimization
- 20 Optimal Control Problems (Dynamic Optimization)
- 21 System Identification and Model Predictive Control
- Index
Summary
This chapter focuses on the formulation of LP problems as a means to teach how to derive mathematical programming formulations for basic descriptions, specifications, and data related to associated processes that are to be optimized.It focuses on basic blending type problems, production planning, with special focus given to network flow problems that cover a wide range of applications.This topic is revisited in more detail in chapter 14.
- Type
- Chapter
- Information
- Optimization for Chemical and Biochemical EngineeringTheory, Algorithms, Modeling and Applications, pp. 133 - 145Publisher: Cambridge University PressPrint publication year: 2021