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Preface
This documentation guides GAMS User through several topics in GAMS system. Some introductions to software systems
are like reference manuals: they describe each command in detail. Others take you step by step through a small number of
examples. This guide uses elements of both approaches.
• Introduction and Tutorial - This is a self-contained tutorial that guides you through a single example, a small
transportation model, in some detail: you can quickly investigate the flavor of GAMS by reading it.
– Introduction - an introductory to GAMS User's Guide.
– Tutorial - A GAMS Tutorial by Richard E. Rosenthal.
![gams正版软件教程](//l.b2b168.com/2021/04/29/13/202104291304363189094.jpg)
A GAMS Tutorial by Richard E. Rosenthal
1 Introduction
The introductory part of this book ends with a detailed example of the use of GAMS for formulating, solving, and analyzing
a small and simple optimization problem. Richard E. Rosenthal of the Naval Postgraduate School in Monterey, California
wrote it. The example is a quick but complete overview of GAMS and its features. Many references are made to other parts
of the book, but they are only to tell you where to look for more details; the material here can be read profitably without
reference to the rest of the book.
The example is an instance of the transportation problem of linear programming, which has historically served as a 'laboratory
animal' in the development of optimization technology. [See, for example, Dantzig (1963) 1. ] It is a good choice for
illustrating the power of algebraic modeling languages like GAMS because the transportation problem, no matter how large
the instance at hand, possesses a simple, exploitable algebraic structure. You will see that almost all of the statements in the
GAMS input file we are about to present would remain unchanged if a much larger transportation problem were considered.
In the familiar transportation problem, we are given the supplies at several plants and the demands at several markets for a
single commodity, and we are given the unit costs of shipping the commodity from plants to markets. The economic question
is: how much shipment should there be between each plant and each market so as to minimize total transport cost?
The algebraic representation of this problem is usually presented in a format similar to the following
![gams正版软件教程](//l.b2b168.com/2021/04/29/13/202104291307029546804.jpg)
These results indicate, for example, that it is optimal to send nothing from Seattle to Topeka, but if you insist on sending one
case it will add .036 $K (or $36.00) to the optimal cost. (Can you prove that this figure is correct from the optimal shipments
and the given data?)
![gams正版软件教程](//l.b2b168.com/2021/04/29/11/202104291132578980334.jpg)
ALPHAECP
AMPL
ANTIGONE 1.1
BARON
BDMLP
BENCH
BONMIN 1.8
CBC 2.9
CONOPT 3
CONOPT 4
CONVERT
COUENNE 0.5
CPLEX 12.7
DE
DECIS
DICOPT
EXAMINER
GAMSCHK
GLOMIQO 2.3
GUROBI 7.0
GUSS
IPOPT 3.12
JAMS
KESTREL
KNITRO 10.0
基于扩展平面切割(ECP)方法的MINLP求解器
在AMPL模型系统中使用求解器时与GAMS模型连接
MINLP确定性全局优化
成熟**解决方案的分支和减少优化向导
任意GAMS系统都配备了LP和MIP求解器
实用方便的GAMS求解器和验证方案
COIN-OR MINLP求解器执行各类分支定界和外逼近算法
高性能LP/MIP求解器
大型的NLP求解器
大型的NLP求解器
将模型转换成其他语言的标量模型的框架
(MI)NLP确定性全局优化
高性能LP/MIP求解器
产生和解决包括EMP/SP中的随机规划的确定等价
大规模随机规划求解器
求解MINLP模型框架
检查解点并评估其优点的工具
GAMS求解线性规划问题时对结构和解决方案属性的检查系统
混合整数二次模型分支定界全局优化
高性能LP/MIP求解器
有效解决多个相关模型实例的框架(收集更新分散的求解方案)
大规模非线性规划的内点优化算法
扩展数学规划求解器(包括LogMIP)
本地GAMS系统使用远程NEOS求解器框架
大型NLP求解器
求解器 描述
03
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