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AMPL 3.5-优化建模工具软件
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AMPL 3.5-优化建模工具软件
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  AMPL-优化建模工具软件

AMPL

AMPL是一套用于优化建模的高级建模工具。AMPL是一种描述并求解大规模复杂数学问题的建模语言。AMPL支持世界上大部分的求解器,如CBC、CPLEX、FortMP、Gurobi、MINOS、IPOPT、SNOPT和KNITRO。AMPL语言的的一个主要的特点是对优化问题的数学表达式的简化,这使得简明地可读地定义优化问题成为可能。根据NEOS的统计AMPL是使用最为广泛的数学模型语言。

在售的求解器(Solver)

线性求解器

这些求解器都处理连续变量和整数变量中的线性和凸二次优化问题:

单个求解器提供其他问题类型的扩展。所有这些都包含用于线性编程的快速原始单纯形,双重单纯形和内部方法,以及用于纯整数和混合整数问题的复杂的分支切割和启发式搜索方法。 包括多个处理器和内核上的并行计算选项。 此类解决方案是商业,政府和研究机构中应用最广泛的应用程序。

非线性求解器

此类别中的求解器为寻找涉及平滑非线性函数(包括比率,多项式,指数和对数以及三角形式)的问题的局部最优解提供了最有效的方法。 它们提供了各种经过验证的算法:

  • CONOPT (ARKI Consulting & Development) — multi-method architecture founded on reduced gradient
  • KNITRO (Ziena Optimization) — choice of interior-point and active-set methods, with support for integer variables and automatic multiple starts
  • LOQO (Princeton University) — interior-point method applied to a sequence of quadratic approximations
  • MINOS (Stanford University) — reduced gradient approach founded on a linear primal simplex method
  • SNOPT (Stanford University) — sequential quadratic approximation method

对于给定的问题类,通常会发现这些求解器方法中的一个或多个是有利的。 非线性求解器广泛用于具有物理组件的能量传输和工程设计等应用,以及先进的经济和金融建模。

替代求解器

这些求解器结合了多种方法来处理由于多个局部最优解,非光滑和离散函数和/或高度组合或逻辑约束而难以实现的优化问题。 我们正在构建此类别的产品,从以下开始:

  • BARON (The Optimization Firm) — Global nonconvex nonlinear optimization in continuous and integer variables
  • LGO (Pintér Consulting) — Global and local optimization over general functional forms

使用AMPL,可以轻松地在相同的模型和数据上尝试多种求解器替代方案,以确定哪种方法最适合给定的应用程序。

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

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.

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.

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.

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.

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).

Hook your own solver to AMPL using our open-source AMPL-solver library.

Supported platforms include Windows, Linux, MacOS, and several Unix-based workstations.

Extensive supporting materials

The AMPL book provides a detailed introductory tutorial plus tutorial introductions to all basic and advanced features.

Numerous examples are available including all models and data from the AMPL book as well as a variety of scripts for common iterative schemes.

The AMPL user forum on Google groups is open to the public for searching or posting.。

 

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