GAMS software and each solver introduction
The General Algebraic Modeling System (GAMS) is an advanced modeling system for mathematical programming and optimization. It consists of a language compiler and a stable integration of various high-performance solvers. GAMS is suitable for complex, large-scale modeling applications and allows you to create large maintenance models to quickly adapt to new situations.
Cutting edge modeling system
Focus on modeling
GAMS allows users to formulate mathematical models to some extent in much the same way as mathematical descriptions. GAMS allows users to focus on modeling and encourages good modeling habits by requiring simple and precise entity and relationship specifications. The GAMS language is similar to the general programming language and is therefore familiar to those with programming experience. Since the way the model is formulated is somewhat similar to its mathematical description, it is not only a programmer, but also an expert in the real world can understand and maintain it. GAMS focuses on modeling and allows to do all the relevant things.
A balanced mix of declarative knowledge and procedural elements allows users to build complex algorithms and even decomposition methods in GAMS. Especially the model for solving the anomaly problem, and the performance problems that come with it.
Design different rules
We try to adapt, not directly.
GAMS focuses on its core competencies: letting users create readable, maintainable models and solve any problems with the best solution. An open architecture and multiple data interfaces allow seamless communication with external systems.
Models, solvers, data, platforms, and user interfaces are all on separate layers, making it easy to switch solvers, use multiple data sets, run on multiple platforms, and integrate GAMS into existing applications, structures, and workflows.
Independent model and solver
Provides over 25 broad and diverse solver combinations, including all expected commercial solvers.
LP/MIP/QCP/MIQCP: CPLEX, GUROBI, MOSEK, XPRESS
NLP: CONOPT, IPOPTH, KNITRO, MINOS, SNOPT
MINLP: ALPHAECP, ANTIGONE, BARON, DICOPT, OQNLP, SBB
Hybrid Complementary Problem Solver (MCP), Balance Constraint Mathematical Programming Solver (MPEC), and Constrained Nonlinear System Solver (CNS)
Free bundled into each GAMS system (such as BONMIN (MINLP), CBC (LP, MIP), COUENNE (MINLP), IPOPT (NLP). The education version also includes SCIP and SOPLEX.
Choosing which solver to use is very simple -- just change one line of code or adjust an option setting. If you want to compare the performance of the solver or see what improvements are possible, you don't need to make any settings. Similarly, model types can be easily switched (eg linear and nonlinear), and it is very easy to try different formulas. By using GAMS, you get a wide range of models and solver environments.
Independent models and data
You can write independent model data, including data from a variety of sources, from ASCII to Excel or Access.
And various other sources. For example, use the GDX (GAMS Data Exchange) file format. GDX files can hold values ​​for one or more GAMS symbols, such as sets, parameter variables, and equations. The GDX file can prepare data for the GAMS model, display the results of the GAMS model, save the results for the same model using different parameters, and so on. GDX files cannot save a model's formula or execute a statement. GDX file binaries can be ported on different platforms.
Independent model and platform
Models are fully portable across platforms—write once and run anywhere.
GAMS runs on Windows, Linux, Mac OS X, SOLARIS, Sparc Solaris and IBM Power AIX.
Independent model and user interface
The object-oriented GAMA API allows GAMS to be seamlessly integrated into applications that provide the right category for interaction. The three object-oriented GAMS APIs are .NET, Java and Python with .NET framework 4 (Visual Studio 2010), Java SE 5 or higher, and Python 3.4, 2.7 and 2.6.
In addition to the object-oriented GAMA API, there are also expert-level (or level) GAMS APIs that require a highly knowledgeable GAMS component library.
In addition to the API, GAMS also provides smart links to applications such as MS Excel, MatLab or R. Users can continue to work in this environment, and all the optimization functions of GAMS can be accessed through an API. This allows model data and results in the application to be visualized and analyzed.
Large, global user community
Multinational companies, schools, research institutions and governments in more than 120 countries use GAMS, including energy and chemical, economic modeling, agricultural planning or manufacturing.
GAMS solver
solver
description
ALPHAECP
MINLP solver based on extended planar cutting (ECP) method
AMPL
Connect to the GAMS model when using the solver in the AMPL model system
ANTIGONE 1.1
MINLP deterministic global optimization
BARON
Branch and Reduce Optimization Wizard for Mature Global Solutions
BDMLP
Any GAMS system is equipped with LP and MIP solvers
BENCH
Practical and convenient GAMS solver and verification scheme
BONMIN 1.8
COIN-OR MINLP solver performs various branch and outer approximation algorithms
CBC 2.9
High performance LP/MIP solver
CONOPT 3
Large NLP solver
CONOPT 4
Large NLP solver
CONVERT
a framework for transforming models into scalar models in other languages
COUENNE 0.5
(MI) NLP deterministic global optimization
CPLEX 12.7
High performance LP/MIP solver
DE
Generate and resolve deterministic equivalence including random programming in EMP/SP
DECIS
Large-scale random programming solver
DICOPT
Solving the MINLP model framework
EXAMINER
Tools to check the solution and evaluate its benefits
GAMSCHK
Inspection system for structure and solution attributes when GAMS solves linear programming problems
GLOMIQO 2.3
Mixed integer quadratic model branch and bound global optimization
GUROBI 7.0
High performance LP/MIP solver
GUSS
Effectively solve the framework of multiple related model instances (collect and update the distributed solution)
IPOPT 3.12
Interior Point Optimization Algorithm for Large Scale Nonlinear Programming
JAMS
Extended Math Solver (including LogMIP)
KESTREL
Local GAMS system uses remote NEOS solver framework
KNITRO 10.0
Large NLP solver
LGO
Global-local nonlinear optimization solution suite
LINDO 10.0
Random solver, including an unlimited version of LINDOGLOBAL
LINDOGLOBAL 10.0
MINLP solver for mature global solutions
LINGO
Using the solver to solve the link to the GAMS model in the LINGO model system
LOCALSOLVER 6.0
Mixed neighborhood search algorithm
LS
GAMS linear regression solver
MILES
MCP solver
MINOS
NLP solver
MOSEK 8
Large LP/MIP plus cone convex nonlinear programming system
MSNLP
Globally optimized multi-start method
NLPEC
Convert MPEC to NLP using other GAMS NLP solvers
OQNLP
Globally optimized multi-header startup method
OsiCplex
Bare-Bone connects to CPLEX
OsiGurobi
Bare-Bone connected to Gurobi
OsiMosek
Bare-Bone connects to Mosek
OsiXpress
Bare-Bone is connected to Xpress
PATHNLP
Large-scale NLP solver for convex problems
PATH
Large scale MCP solver
PYOMO
Using the solver to solve the link to the GAMS model in the PYOMO model system
SBB
Branch and Bound Algorithm for Solving MINLP Model
SCIP 3.2
High performance constrained integer programming solver
SNOPT
Large-scale SQP algorithm based on NLP solver
SOPLEX 2.2
High performance LP solver
XA
Large scale LP/MIP solver
XPRESS 28.01
High performance LP/MIP solver
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