Mathematical modeling and optimization analysis based on general optimization software gams

Optimization analysis is an important problem in many fields , The general way to solve optimization problems is ： Build a model 、 Write algorithms 、 Solving the problem . Common types of problems are linear programming 、 Nonlinear programming 、 mixed integer programming 、 Mixed integer nonlinear programming 、 Secondary planning, etc , Optimization algorithm includes artificial intelligence algorithm, interior point method and other mathematical optimization methods . Algorithm writing is a complicated process , This is especially true for large-scale and complex optimization problems , And the parameter setting of the same algorithm when dealing with different problems 、 The change of architecture is relatively inconvenient . and GAMS As a powerful general algebraic modeling and optimization software , To be able to turn complexity into simplicity , Avoid complex algorithm Writing , Focus users' attention more on models than algorithms , It brings great convenience to solve various optimization problems . To help researchers in various fields master GAMS The use of this powerful optimization tool , Better solve professional problems , The course content includes the introduction of typical optimization models and algorithms 、GAMS Installation and introduction 、GAMS Programming 、GAMS Program debugging 、 There are five chapters including practical application example demonstration and experience sharing , In addition to the general case display, the example also covers the case based on GAMS Practical application case analysis of .GAMS Is a general optimization software , Therefore, the content is suitable for workers engaged in optimization research in various fields , It is helpful for researchers in various fields to efficiently deal with various complex optimization problems in this field .

Typical optimization model 、 Algorithm Explain and

be based on GAMS Advantages of optimization analysis

Typical optimization model （LP、NLP、MIP、MINLP、MIQCP etc. ）

Artificial intelligence algorithm （ Genetic algorithm (ga) 、 Ant colony algorithm 、 Tabu search, etc ）

Mathematical optimization methods （ Branch and bound method 、 Dynamic programming 、 Lagrange relaxation method 、 Interior point method 、 Benders Decomposition method, etc ）

be based on GAMS Advantages of mathematical modeling and optimization analysis

GAMS Installation and interface

One 、GAMS install       Two 、File function       3、 ... and 、Edit function       Four 、Search function       5、 ... and 、Windows function      

6、 ... and 、Model Libraries model base Help function

GAMS Programming

Model composition         Programming principles      

Set up a collection Set     1. Static collection      2. Multiple sets      3. Dynamic collection      4. Ordered set （SOS1、SOS2）   

Input parameters Parameter    1. General scalar      2. Index parameters     3. Table parameters      4. Data import （Excel Tabular data ） 5. parameter assignment

Set a variable Variable   1. General scalar     2. Index parameters     3. Table parameters     4. Data import （Excel Tabular data ） 5. parameter assignment

Construction equation Equation    1. Equation definition     2. Equation relation symbol     3. Function and operation expression      4. Scalar equation     5. Index equation

6. Conditional equation （ Under controlled conditions $）

Calculation model Model solve    1. Classification and solution of models    2. Calculation parameter setting （Options）   3. solver (Solver) Comparative analysis and selection of

Display the results Display    1. Variable result display     2. Parameter display General example demonstration

GAMS Program debugging

Check the calculation log     Analysis solution report       Program debugging method

Practical application examples and experience sharing

be based on GAMS Optimization instance sharing         Precautions for common expressions       Other methods of property modification      

Other software calls GAMS