MathOptimizer Professional
für stetige globale und konvexe Optimierung
MathOptimizer Professional (MOP) ist eine hochentwickelte Optimierungsumgebung für Mathematica mit einem externen LGO Solver Link. MOP ermöglicht die globale und lokale Lösung einer allgemeinen Klasse von Optimierungsproblemen.
MathOptimizer Professional kombiniert die Stärken von Mathematica mit der etablierten und externen LGO (Lipschitz Global Optimizer) Solver-Suite. Diese Kombination ermöglicht und bietet ausgereifte Applikation-Entwicklungswerkzeuge, eine Solver-Funktionalität und Lösungsgeschwindigkeit, die vergleichbar ist zu anderen Compiler-basierten oder Optimierungsmodellierungssprachen Implementierungen.
Veröffentlichung Nonlinear Optimization in Mathematica with MathOptimizer Professional
How it works
MathOptimizer Professional
In use for about two decades, the LGO global-local solver engine is currently available for professional C and Fortran compiler platforms, with links to Excel and several prominent optimization modeling languages and technical computing systems. MathOptimizer Professional is the Mathematica-specific implementation of LGO, used with an external C or Fortran compiler.
With MathOptimizer Professional, optimization models are set up in Mathematica in a standardized form, then the following steps are executed automatically (without user interaction):
- the user's Mathematica model is translated to C or Fortran
- a model function dll and an input parameter file are created
- the model function dll is called iteratively by the LGO solver (executable file)
- optimization results are generated by LGO
- the results are written back to the Mathematica notebook of the user.
As a result, one can solve sizeable nonlinear models formulated in Mathematica. LGO per se has been used to solve models in thousands of variables and constraints. Available for a range of C and Fortran compiler platforms.
MathOptimizer
The MathOptimizer global-local solver suite is a different product written entirely in Mathematica.
Both MathOptimizer and MathOptimizer Professional work with all Mathematica versions since release 4. Higher Mathematica releases are recommended for maximal program executionspeed.
Umfangreiche Einführung und Erläuterung finden Sie hier .
Dokumentation
MathOptimizer Professional enthält eine Anleitung mit kurzgefassten Anmerkungungen zum mathematischen Hintergrund und nützliche Tipps zur Modellierung, Testaufgaben und eine umfangreiche Sammlung nicht-trivialer Anwendungsbeispiele. Auf diese Anleitung kann direkt über Mathematicas online Hilfesystem zugegriffen werden.
Additional details are presented in the forthcoming book Advanced Optimization with Mathematica: Scientific, Engineering, and Economic Applications as well as in other related publications and software implementations.
Product Development and Support
MathOptimizer is developed and supported by János D. Pintér. MathOptimizer Professional is developed and supported by János D. Pintér and Frank J. Kampas.
János D. Pintér is a researcher and software developer in the area of nonlinear optimization. He received the 2000 INFORMS Computing Society Prize for Research Excellence for his book Global Optimization in Action and has authored and edited other books and numerous articles related to this field. Dr. Pintér serves on the editorial board of several professional journals. He develops algorithms and software for advanced nonlinear (global, local, combinatorial) optimization.
Frank J. Kampas is a researcher and senior developer at WAM Systems, inc., where he is responsible for adding optimization capabilities to the company's supply-chain management software. He has extensive experience related to programming, model development, and optimization in Mathematica and other languages. He is the developer of the link between Mathematica and LGO.
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