Aimms Optimization ModelingThe AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent. |
Contents
Introduction to Optimization Modeling | 3 |
Formulating Optimization Models | 14 |
Algebraic Representation of Models | 33 |
Sensitivity Analysis | 42 |
Network Flow Models | 53 |
General Optimization Modeling Tricks | 65 |
Integer Linear Programming Tricks | 77 |
Basic Optimization Modeling Applications | 91 |
Intermediate Optimization Modeling Applications | 139 |
A TwoLevel Decision Problem | 149 |
A Bandwidth Allocation Problem | 163 |
A Power System Expansion Problem | 173 |
An Inventory Control Problem | 186 |
Advanced Optimization Modeling Applications | 201 |
A File Merge Problem | 227 |
A Cutting Stock Problem | 241 |
A Media Selection Problem | 100 |
A Diet Problem | 109 |
A Farm Planning Problem | 117 |
A Pooling Problem | 127 |
A Telecommunication Network Problem | 251 |
A Facility Location Problem | 264 |
Appendices | 287 |
Other editions - View all
Common terms and phrases
added addition Aimms algorithm amount applications approach associated assumed becomes bound capacity changes chapter chips coefficients companies computational condition Consider constraints contains corresponding cost decision demand denote described determine distribution equal example expected expression families feasible Figure final flow formulation fraction given illustrated Implement increase indicates inequality initial instance integer integer programming interval introduced investment limited linear programming lower mathematical measure method Minimize nodes notation Note objective function optimal optimal solution optimization model parameters particular path period pool portfolio positive possible practical presented problem production profit programming model records reduced referred restriction result risk scenarios selected shadow prices simplex method solution solved specified stochastic programming Subject Summary supply symbolic Table tion unit variables waste