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  GAMS 运筹规划分析软件|数学规划和最优化程序包

GAMS系统

   内容

介绍
系统特征
2.50版26.1.0(MR)(2019年2月2日)
一个完整的示例
支持的模型类型


   介绍

通用代数建模系统(GAMS)是特别为建模线性,非线性和混合整数最优化问题而设计的.本系统对于大型的,复杂的问题特别有帮助.GAMS可以运行在个人计算机,工作站,大型机和超级计算机上.

GAMS允许使用者通过制定简单的设置来把精力放在建模问题上.至于特定机器和系统软件执行的费时的细节将由GAMS系统来处理.

GAMS对于处理大型的,复杂的,需要多次修订才能最终确定精确模型的独一无二的问题特别有帮助.系统以高度简洁和自然的方式来建模问题.使用者能够快速和方便的更改公式,能从一个求解器转到另一个,甚至稍加费心就能从线性转换到非线性.有关GAMS系统中求解器的简短介绍请点击

   系统特征

GAMS让使用者把精力集中到建模上.通过排除考虑纯技术上的机器特定的问题的需要,比如地址计算,存储分配,子程序链接,和输入输出和流程控制,GAMS增加了用于概念化和运行模型,和分析结果的时间.GAMS本身构建了良好的建模习惯,通过请求简明而精确的实体和关系的规范.GAMS语言形式上和通常使用的编程语言相似.因此对于那些有编程检验的使用者将非常熟悉.

使用GAMS,数据仅仅需要一次就能在熟悉的列表和表格形式中输入.模型以简练的代数声明来描述,对于人和机器都很容易读懂.非常相关的约束的整个集合都被输入到一个声明中.GAMS自动生成每个约束等式,并让使用者处理例外情况,假使那里一般来说是不需要的.在模型中的声明能够被重用,而不需要更改代数式,当其它的实例是相同的或出现了相关问题.错误的位置和类型会在尝试解决方案前被查明.GAMS处理动态模型,包括时间序列,滞后,及暂时终点的提示和处理.

GAMS是灵活而强大的.模型可以非常方便的从一个计算机平台移到另外一个,只要GAMS已经在每个平台被安装好.GAMS很容易进行敏感度分析.使用者能够方便的规划模型来求解一个成分的不同值,然后生成一个输出报告,列出了每种情况的解决方案特征.模型能够同时被开发和文档化,因为GAMS允许使用者包含解释性的文本来作为任意符号和等式的定义和解释.

   2.50版本

GAMS不断的在被增强和扩展.2.50版24分发版本包含了众多更新和增强,比如,提供面对对象的.NET API,gamsbatch批处理脚本,设置最优解范围,用以调用Lindo抽样程序的新的函数库lsadclib,以及在求解器方面的众多更新。更多内容请点击24.8.5分发最近更新

   一个完整的示例

从著名的1963书(由George Dantzig编写)中提取的一个运输问题,用来描述GAMS的有效性.这个模型只是模型库中的部分,模型库中还包含了大量的完整GAMS模型.

   支持模型的类型

GAMS模型类型包括LP,MIP和NLPs的不同形式.这里列出了GAMS支持的所有的模型类型.

The General Algebraic Modeling System (GAMS) is a high-level modeling system for mathematical programming and optimization. It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations. GAMS is specifically designed for modeling linear, nonlinear and mixed integer optimization problems.

Cutting Edge Modeling
Focusing on the modeler

GAMS allows its users to formulate mathematical models in a way that is very similar to their mathematical description. Take a look at this simple example that illustrates the basic structure and characteristics of a GAMS model and how it relates to the mathematical formulation. The GAMS Tutorial explains the same model in a more extensive way, or take a look at this video on our YouTube channel.

Through this, GAMS lets the user concentrate on modeling. GAMS encourages good modeling habits itself by requiring concise and exact specification of entities and relationships. The GAMS language is formally similar to common programming languages. It is therefore familiar to anyone with programming experience. But since the model is formulated in a way that is similar to its mathematical description, it can be understood and maintained not only by programmers, but also by the actual domain experts. GAMS focuses on the modeler and allows him to do all relevant things himself.

The balanced mix of declarative and procedural elements allows building complex algorithms and even the implementation of decomposition methods in GAMS. This is especially relevant for models addressing unusual problems that oftentimes come along with performance issues.

Design Principles That Make a Difference
"We make an effort to fit in, rather than take over."

GAMS focuses on its core competence: empowering our users to build readable, maintainable models and to solve them with the best solvers available anywhere. Our open architecture and the many data interfaces provided allow seamless communication with external systems.
Model, solver, data, platform and user interface are separated in independent layers, making it easy to switch a solver, use multiple data sets, run on multiple platforms, and integrate GAMS into existing applications, structures, and workflows.

Independence of Model and Solver
We offer an exceptionally extensive and diverse portfolio of more than 25 solvers, including all the expected commercial solvers.

LP/MIP/QCP/MIQCP: CPLEX, GUROBI, MOSEK, XPRESS
NLP: CONOPT, IPOPTH, KNITRO, MINOS, SNOPT
MINLP: ALPHAECP, ANTIGONE, BARON, DICOPT, OQNLP, SBB
Solvers for Mixed Complementarity Problems (MCP), Mathematical Programs with Equilibrium Constraints (MPEC), and Constrained Nonlinear Systems (CNS)
Free alternatives bundled with every GAMS system (e.g. BONMIN (MINLP), CBC (LP, MIP), COUENNE (MINLP), IPOPT (NLP); for academic licenses also SCIP and SOPLEX
See our documentation or our price list for a full list of the available solvers.

Selecting the solver to use is simple - just change one line of code or adjust one option setting. No need to reimplement anything in order to compare solver performance or see what improvements are possible. Similarly, you can switch easily between model types (e.g. linear and nonlinear), so experimenting with different formulations is easy.

With GAMS, you get one environment for a wide range of model types and solvers.

Independence of Model and Data
You can write the model independently of the data, and include data from many different kinds of sources, from plain ASCII to Excel or Access and many others, for example using the GDX (GAMS Data eXchange) file format.

A GDX file is a file that stores the values of one or more GAMS symbols such as sets, parameters variables and equations. GDX files can be used to prepare data for a GAMS model, present results of a GAMS model, store results of the same model using different parameters etc. A GDX file does not store a model formulation or executable statements.

GDX files are binary files that are portable between different platforms.

The video GAMS and Excel - Using GDX to Transfer Data on our YouTube channel illustrates this for Excel.

Independence of Model and Platform
Models are fully portable between platforms - write once, run anywhere.
GAMS runs on Windows, Linux, Mac OS X, SOLARIS, Sparc Solaris, and IBM Power AIX.

Independence of Model and User Interface
The GAMS object-oriented APIs allow the seamless integration of GAMS into an application by providing appropriate classes for the interaction with GAMS. The three versions of the object-oriented GAMS API: .NET, Java, and Python work with .NET framework 4 (Visual Studio 2010), Java SE 5 and up, as well as Python 3.4, 2.7, and 2.6 accordingly.

In addition to the object-oriented GAMS APIs, there are expert-level (or low-level) GAMS APIs whose usage requires advanced knowledge of GAMS component libraries. See our documentation for further information on the APIs.

In addition to the APIs, GAMS offers smart links to applications like MS Excel, MatLab, or R. Through these, the user can keep working in his productive tool environment, while the application accesses all optimization capabilites of GAMS through an API. This allows for example the visualization and analyses of model data and results in the application.

Large, Global User Community
GAMS is used in more than 120 countries by multinational companies, universities, research institutions and governments in many different areas, including the energy and chemical industries, for economic modelling, agricultural planning, or manufacturing.

Check out our Case Studies to see what our users are doing with GAMS around the world.

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  • 400-621-1085 021-50391085

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GAMS:概述
最近更新:26.1.0分发
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