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软件试用 AMPL—运筹学集成建模和优化平台

软件简介


强大的建模语言和高效的表达方式让 AMPL 成为运筹学建模软件的经典。坐拥谷歌和百度运筹学建模软件搜索第一位,容易学习、资料完备让 AMPL 拥有全球最大的学校科研群体。回归运筹学本质,体验 AMPL 的强大,迈出运筹学学习第一步。

AMPL教育版本

你也许拥有Lingo, iLog Cplex 或者 Fico Xpress,但它们只包含自身的优化器,只能解决几种有限运筹学优化模型。而 AMPL 学校版则包含了多个全功能、全球顶尖优化器,可以解决多种运筹学问题类型。

该平台包括:
不限用户数量网络版AMPL建模环境,内嵌全功能优化器,可以解决线性(LP)、混合整数(MIP)、非线性(NLP)、二次型(QP)、二次型混合整数(MIQP)、二次型约束(QCP)、二次型整数约束(MIQCP)、混合互补问题(MCP)、约束互补问题(MPCC)、混合整数非线性(MINLP)、约束规划(CP)问题,包括Gurobi, Cplex(含CP), COIN-OR solvers, CBC, Ipopt, Bonmin, Couenne 等。

用户可以在优化器之间自由转换。

这个平台的显著特点就是支持海量并发用户数量,并且所含优化器和建模环境都具备商业版的全部功能。 用户可以自由在多个优化器之间切换,解决各种运筹学优化问题。

软件功能


AMPL 与其它优化建模环境相比,具有突出的优势:
● 简单、实用、学习容易,尤其适合短课时教学。简单培训后就可以开始建立复杂模型和解决问题。
● 提供完整和强大的建模语言,可以求解线性和非线性问题。
● 语言规范源于贝尔实验室,建模语言采用与自然代数语言极为相近的表达和书写方式。
● 广泛支持各种集合定义和运算符,支持多维集合,支持排序、未排序、循环集合,以及支持数字和对象集合。
● 提供基于Windows, Linux 平台的可视化集成开发环境 IDE。
● 对于非线性问题,提供初始化原始和对偶数值,高阶导数,自定义函数等功能。
● 支持网络规划中弧和节点的直接定义,以及分段线性函数定义。
● 提供命令行交互模式,可以方便批处理多个模型和数据。
● 支持循环和条件执行语句,便于控制多次优化进程。

AMPL链接的商业优化器

AMPL 可以直接调用很多顶尖商业优化器和免费的开源优化器。其中商业优化器包括
(优化器名称及解决问题类型)

GUROBI
Linear and convex quadratic optimization in continuous and integer variables.

CPLEX(含CP)
Linear and convex quadratic optimization in continuous and integer variables; constraint programming

MINOS
Linear, quadratic, and smooth nonlinear objectives and constraints in continuous variables.

CONOPT
Linear, quadratic, and general smooth nonlinear objectives and constraints in continuous variables.

SNOPT
Linear, quadratic, and smooth nonlinear objectives and constraints in continuous variables.

KNITRO
Linear, quadratic, and general smooth nonlinear optimization in continuous and integer variables.

英文简介


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.