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AMPL是一个复杂的建模工具，支持整个建模周期：开发、测试、部署和守护。通过使用与人们思虑优化模型一样的方式来暗示优化模型的暗示，AMPL推进了急剧开发和可高的了局。

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AMPL集成了用于描述优化数据、变量、指标和约束的建模说话
；用于浏览模型和分析了局的号令说话
；以及用于网络和操作及实现迭代规划的剧本说话。这些都使用一样的概想和语法来简化用于法式构建。

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建模说话职能

• 对集中和集中运算符的宽泛支持。AMPL模型能够使用对、三元组和更长元组的集中
  ；在集中上索引的集中
  ；无序，有序和循环的对象集
  ；和数组。

• 算术、逻辑和前提表白式的通用和天然语法
  ；求和和其他迭代运算符的熟悉约定。

• 自动处置陆续和整数变量中的线性和凸二次问题。

• 非线性编程个性，例如初始原始值和对偶值、用户界说函数、急剧自动微分以及“界说”变量的自动解除。

• 网络流、分段线性、互补前提和逻辑寓意的方便代替暗示法。

有价值的建模支持职能：

• 拥有批处置选项的交互式号令环境。显示号令可让您查看全数模型组件或表白式，在屏幕上浏览或写入文件，使用自动体式化或您自己的偏好。

• 剧本说话，蕴含循环和if-then-else号令。AMPL号令云说话中的法式能够界说复杂的迭代规划，以处置输入数据、反复调整和解决多个模型的事俘，并为分析筹备了局。

• 模型和数据的分离。即便集中和数据表不休增长，AMPL模型依然维持简洁。模型能够蕴含多种数据有效性的前提。

• 数据输入和输出的衔接。简洁的语句将模型数据和了局与关系数据表的内容联系起来。

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宽泛的可用性

可用的求解器蕴含盛行和强的优化引擎：

• 陆续和混合整数问题的线性和凸二次求解器（CPLEX、Gurobi、Xpress）。

• 陆续问题（CONOPT、Ipopt、KNITRO、MINOS、SNOPT）和混合整数问题（Bonmin、Couenne、KNITRO）的部门解的非线性求解器。

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为什么选择AMPL？

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AMPL系统以一种推进急剧开发和靠得住了局的集成方式支持整个优化建模性命周期—造订、测试、部署和守护。AMPL使用高档代数暗示来描述优化模型的方式与人们对优化模型的见解一样，它可以为您提供成功执行大规模优化项目所需的先机。

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AMPL将其建模说话与用于分析和调试的号令说话以及用于操作数据和执行优化战术的剧本说话集成在一路。全数这些都使用一样的概想来推进简化模型构建。

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当您将优化模型嵌入利用法式并将其部署到企业系统中时，AMPL的C++、C#、Java、MATLAB、Python和RAPI可确保您占有靠得住且可守护的实现。

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支持的平台蕴含 Windows、Linux、MacOS 和几个基于 Unix 的工作站。

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【英文介绍】

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The AMPL system is a sophisticated modeling tool that supports the entire optimization modeling lifecycle: development, testing, deployment, and maintenance.

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By using a high-level representation that represents optimization models in the same ways that people think about them, AMPL promotes rapid development and reliable results.

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AMPL integrates a modeling language for describing optimization data, variables, objectives, and constraints; a command language for browsing models and analyzing results; and a scripting language for gathering and manipulating data and for implementing iterative optimization schemes. All use the same concepts and syntax for streamlined application-building.

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Powerful modeling language features

• Broad support for sets and set operators. AMPL models can use sets of pairs, triples, and longer tuples; collections of sets indexed over sets; unordered, ordered, and circular sets of objects; and sets of numbers.

• General and natural syntax for arithmetic, logical, and conditional expressions; familiar conventions for summations and other iterated operators.

• Automatic handling of linear and convex quadratic problems in continuous and integer variables.

• Nonlinear programming features such as initial primal and dual values, user-defined functions, fast automatic differentiation, and automatic elimination of “defined” variables.

• Convenient alternative notations for network flows, piecewise-linearities, complementarity conditions, and logical implications.

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Valuable modeling support features

• Interactive command environment with batch processing options. Powerful display commands let you view any model component or expression, browsing on-screen or writing to a file, using automatic formatting or your own preferences.

• Powerful scripting language including looping and if-then-else commands. Programs in the AMPL command language can define sophisticated iterative schemes that process input data, repeatedly adjust and solve instances of multiple models, and prepare results for analysis.

• Separation of model and data. AMPL models remain concise even as sets and data tables grow. Models may incorporate many kinds of conditions for validity of the data.

• Data input and output connections. Concise statements relate the model data and results to the contents of relational data tables.

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Broad availability

• Available solvers include the most popular and powerful optimization engines:

• Linear and convex quadratic solvers for both continuous and mixed-integer problems (CPLEX, Gurobi, Xpress).

• Nonlinear solvers for local solution of continuous problems (CONOPT, Ipopt, KNITRO, MINOS, SNOPT) and mixed-integer problems (Bonmin, Couenne, KNITRO).