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AMPL—運籌學集成建模和優化平臺

軟件試用 獲取報價

軟件簡介

強大的建模語言和高效的表達方式讓 AMPL 成為運籌學建模軟件的經典。坐擁谷歌和百度運籌學建模軟件搜索第一位，容易學習、資料完備讓 AMPL 擁有全球最大的學?？蒲腥后w?；貧w運籌學本質，體驗 AMPL 的強大，邁出運籌學學習第一步。

AMPL教育版本

你也許擁有Lingo, iLog Cplex 或者 Fico Xpress，但它們只包含自身的優化器，只能解決幾種有限運籌學優化模型。而 AMPL 學校版則包含了多個全功能、全球頂尖優化器，可以解決多種運籌學問題類型。

該平臺包括：
不限用戶數量網絡版AMPL建模環境，內嵌全功能優化器，可以解決線性（LP）、混合整數（MIP）、非線性（NLP）、二次型（QP）、二次型混合整數（MIQP）、二次型約束（QCP）、二次型整數約束（MIQCP）、混合互補問題（MCP）、約束互補問題（MPCC）、混合整數非線性（MINLP）、約束規劃（CP）問題，包括Gurobi, Cplex（含CP）, COIN-OR solvers, CBC, Ipopt, Bonmin, Couenne 等。

用戶可以在優化器之間自由轉換。

這個平臺的顯著特點就是支持海量并發用戶數量，并且所含優化器和建模環境都具備商業版的全部功能。 用戶可以自由在多個優化器之間切換，解決各種運籌學優化問題。

軟件功能

AMPL 與其它優化建模環境相比，具有突出的優勢：
● 簡單、實用、學習容易，尤其適合短課時教學。簡單培訓后就可以開始建立復雜模型和解決問題。
● 提供完整和強大的建模語言，可以求解線性和非線性問題。
● 語言規范源于貝爾實驗室，建模語言采用與自然代數語言極為相近的表達和書寫方式。
● 廣泛支持各種集合定義和運算符，支持多維集合，支持排序、未排序、循環集合，以及支持數字和對象集合。
● 提供基于Windows, Linux 平臺的可視化集成開發環境 IDE。
● 對于非線性問題，提供初始化原始和對偶數值，高階導數，自定義函數等功能。
● 支持網絡規劃中弧和節點的直接定義，以及分段線性函數定義。
● 提供命令行交互模式，可以方便批處理多個模型和數據。
● 支持循環和條件執行語句，便于控制多次優化進程。

AMPL鏈接的商業優化器

AMPL 可以直接調用很多頂尖商業優化器和免費的開源優化器。其中商業優化器包括
（優化器名稱及解決問題類型）

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.

英文簡介

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.

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