GAMS

https://www.gams.com/latest/docs
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### Getting Started Examples

Source: https://www.gams.com/latest/docs/UG_GAMSCONNECT.html

Introduction to the basic functionalities of GAMS Connect agents through simple examples.

```APIDOC
## Getting Started Examples

This section introduces the basic functionalities of GAMS Connect agents on some simple examples. For more examples, refer to the 'Examples' section.
```

--------------------------------

### Install GAMS Python API

Source: https://www.gams.com/latest/docs/RN_240.html

Use the setup script to install the GAMS Python API into the local environment.

```bash
   cd <Path/To/GAMS>/apifiles/Python/api && python setup.py install && cd ..
```

--------------------------------

### CPLEX solver options file example

Source: https://www.gams.com/latest/docs/UG_SolverUsage.html

This example shows a typical CPLEX options file. Lines starting with '*' are comments. Options like 'barrier' and 'crossover 2' configure the solver's behavior.

```text
* CPLEX options file
barrier
crossover 2

```

--------------------------------

### CSV2GDX Getting Started

Source: https://www.gams.com/latest/docs/T_CSV2GDX.html

Introduction to the basic functionalities of CSV2GDX with examples, highlighting its utility for specific CSV file structures.

```APIDOC
## Getting Started with CSV2GDX

### Description
This section introduces the fundamental capabilities of the `CSV2GDX` tool through simple examples. It emphasizes scenarios where `CSV2GDX` is particularly useful, such as processing files with non-standard delimiters or decimal separators, which are challenging for GAMS's built-in `table` statement.

### Key Use Cases

- **Non-Standard Delimiters**: Reading CSV files that use delimiters other than commas (e.g., semicolons or tabs).
- **Decimal Separators**: Handling CSV files where decimals are denoted by commas instead of periods.
- **Enhanced Data Import**: Provides features beyond the standard `table` statement for more complex CSV data import into GAMS.

```

--------------------------------

### Transport5 Example - C# Source File

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/classTransportSeq_1_1Transport5.html

This is the source file for the Transport5 example, which is the 5th in a series of tutorial examples. It shows how to initialize a GAMSCheckpoint by running a GAMSJob and how to initialize a GAMSJob from a GAMSCheckpoint.

```csharp
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

using Gams;

namespace Transport5
{
    class Program
    {
        static void Main(string[] args)
        {
            // Initialize GAMS
            var gams = new GamsMi();

            // Create a GAMSJob from a GDX file
            var job = new GamsJob(gams, "transport.gms");

            // Run the job and create a GAMSCheckpoint
            var checkpoint = job.RunToCheckpoint();

            // Create a new GAMSJob from the GAMSCheckpoint
            var job2 = new GamsJob(gams, checkpoint);

            // Run the new job
            job2.Run();

            // Dispose GAMS
            gams.Dispose();
        }
    }
}
```

--------------------------------

### GAMS Python API

Source: https://www.gams.com/latest/docs/apis/python/functions_t.html

Documentation for the GAMS Python API, including getting started, control, magic, transfer, and examples.

```APIDOC
## GAMS Python API

### Description
Documentation for the GAMS Python API, covering its usage, control mechanisms, and examples.

### Getting Started
Information on how to begin using the GAMS Python API.

### Control
Details on controlling GAMS functionalities through the Python API.

#### Classes

##### Class List
List of all available classes.

##### Class Index
Index of all available classes.

##### Class Hierarchy
Hierarchy of all available classes.

##### Class Members
Details on members within classes.

###### All
Lists all members.

###### Functions
Lists all functions.

###### Variables
Lists all variables.

###### Properties
Lists all properties.

### Magic (Jupyter Notebooks)
Information on using GAMS within Jupyter Notebooks.

### Transfer
Details on data transfer functionalities.

### Examples
Code examples demonstrating the usage of the GAMS Python API.
```

--------------------------------

### Example SBB Configuration

Source: https://www.gams.com/latest/docs/S_SBB.html

An example configuration file specifying NLP subsolvers and log frequency.

```text
   rootsolver conopt.1
   subsolver snopt
   loginterval 10
```

--------------------------------

### GAMS API - Python API

Source: https://www.gams.com/latest/docs/apis/python/functions_g.html

Documentation for the GAMS Python API, including getting started, control, transfer, and examples.

```APIDOC
## GAMS API - Python API

### Description
Documentation for the GAMS Python API, covering its usage for controlling GAMS execution, data transfer, and providing examples.

### Sub-sections
- Getting Started
- Control
  - Classes
    - Class List
    - Class Index
    - Class Hierarchy
    - Class Members
      - All
      - Functions
      - Variables
      - Properties
- Magic (Jupyter Notebooks)
- Transfer
- Examples
```

--------------------------------

### Parameter Output Examples

Source: https://www.gams.com/latest/docs/T_CSV2GDX.html

Displays the structure of parameters before and after applying valueDim and performing calculations.

```text
----     36 PARAMETER d  distance in thousands of miles

             new-york     chicago      topeka

seattle         2.500       1.700       1.800
san-diego       2.500       1.800       1.400

```

```text
----     49 PARAMETER dmod 

                         miles

seattle  .new-york       2.500
seattle  .chicago        1.700
seattle  .topeka         1.800
san-diego.new-york       2.500
san-diego.chicago        1.800
san-diego.topeka         1.400

```

```text
----     52 PARAMETER dmod

                         miles          km

seattle  .new-york       2.500       4.630
seattle  .chicago        1.700       3.148
seattle  .topeka         1.800       3.334
san-diego.new-york       2.500       4.630
san-diego.chicago        1.800       3.334
san-diego.topeka         1.400       2.593

```

--------------------------------

### Run Connect from Command Line

Source: https://www.gams.com/latest/docs/UG_GAMSCONNECT.html

Demonstrates how to execute Connect instructions using a YAML file from the command line. Supports passing key-value substitutions.

```Shell
gamsconnect <YAMLFile> [key1=value1 [key2=value2 [key3=value3 [...]]]]

```

--------------------------------

### Matlab API - Control

Source: https://www.gams.com/latest/docs/apis/matlab_control/functions_vars_f.html

Documentation for the GAMS Matlab Control API, including getting started, tutorials, classes, and examples.

```APIDOC
## Matlab API - Control

### Description
Provides programmatic control over GAMS from Matlab.

### Endpoint
N/A (Library-based API)

### Parameters
N/A

### Request Example
N/A

### Response
N/A

## Matlab API - Class Members

### Description
Lists documented variables within the GAMS Matlab API, categorized by class.

### Method
N/A

### Endpoint
N/A

### Parameters
N/A

### Request Body
N/A

### Response
N/A

## Class: matlab.gams.control.Options

### Description
Contains options for controlling GAMS execution via the Matlab API.

### Variables
- **FDDelta** (Type: Unknown) - Description: Unknown
- **FDOpt** (Type: Unknown) - Description: Unknown
- **FErr** (Type: Unknown) - Description: Unknown
- **FGHNumericNoScale** (Type: Unknown) - Description: Unknown
- **FGHNumericScale** (Type: Unknown) - Description: Unknown
- **FILE_SEPARATOR** (Type: Unknown) - Description: Unknown
- **fileCase** (Type: Unknown) - Description: Unknown
- **fileName** (Type: Unknown) - Description: Unknown
- **FileOperationsAcceptedParameters** (Type: Unknown) - Description: Unknown
- **fileStem** (Type: Unknown) - Description: Unknown
- **fileStemApFromEnv** (Type: Unknown) - Description: Unknown
- **filtered** (Type: Unknown) - Description: Unknown
- **FirstRecord** (Type: Unknown) - Description: Unknown
- **firstRecord** (Type: Unknown) - Description: Unknown
- **FIXED** (Type: Unknown) - Description: Unknown
- **FixedVarsNotTreatedAsConstants** (Type: Unknown) - Description: Unknown
- **FixedVarsTreatedAsConstants** (Type: Unknown) - Description: Unknown
- **FollowingError** (Type: Unknown) - Description: Unknown
- **forceOptFile** (Type: Unknown) - Description: Unknown
- **forceWork** (Type: Unknown) - Description: Unknown
- **ForE** (Type: Unknown) - Description: Unknown
- **ForEFloatingDec** (Type: Unknown) - Description: Unknown
- **forLim** (Type: Unknown) - Description: Unknown
- **FormfeedCharNewPage** (Type: Unknown) - Description: Unknown
- **FortranStyle** (Type: Unknown) - Description: Unknown
- **FREE** (Type: Unknown) - Description: Unknown
- **freeEmbeddedPython** (Type: Unknown) - Description: Unknown
- **full** (Type: Unknown) - Description: Unknown

### Request Example
N/A

### Response Example
N/A
```

--------------------------------

### Execute GAMS C++ Example on Windows

Source: https://www.gams.com/latest/docs/API_CPP_TUTORIAL.html

Sets the library path and executes the transport1 example binary.

```bash
cd transport1\Release
set PATH=%PATH%;<GAMS system directory>\apifiles\C++\lib\vs2019
transport1.exe
```

--------------------------------

### GAMS Python API

Source: https://www.gams.com/latest/docs/apis/python/functions_vars_u.html

Documentation for the GAMS Python API, including getting started, control, magic (Jupyter Notebooks), transfer, and examples.

```APIDOC
## GAMS Python API

### Description
Documentation for the GAMS Python API, covering its usage for controlling GAMS models and data transfer.

### Getting Started
Information on how to begin using the Python API.

### Control
Details on controlling GAMS execution and model parameters via the Python API.

#### Classes

##### Class List
Provides a list of all available classes.

##### Class Index
An index of all classes.

##### Class Hierarchy
Shows the inheritance hierarchy of classes.

##### Class Members

###### Functions
Lists all documented functions.

###### Variables
Lists all documented variables, including their class and type.

* **Unbounded** (gams.control.workspace.ModelStat)
* **UnboundedNoSolution** (gams.control.workspace.ModelStat)
* **UnexpectedCmexRC** (gams.control.workspace.GamsExitCode)
* **Unknown** (gams.control.workspace.VarType)
* **Upper** (gams.control.execution.UpdateAction)
* **UpperCase** (gams.control.options.Case, gams.control.options.FileCase)
* **UpperCaseFileOnly** (gams.control.options.FileCase)
* **User** (gams.control.workspace.SolveStat)

###### Properties
Lists all documented properties.

### Magic (Jupyter Notebooks)
Guidance on using the GAMS API within Jupyter Notebooks.

### Transfer
Information on data transfer functionalities.

### Examples
Code examples demonstrating various use cases of the Python API.
```

--------------------------------

### Initialize Save/Restart Process

Source: https://www.gams.com/latest/docs/API_DOTNET_TUTORIAL.html

Sets up the working directory and initiates the creation of the save/restart file.

```csharp
string wDir = Path.Combine(".", "tmp");
CreateSaveRestart(Path.Combine(wDir, "tbase"));
```

--------------------------------

### Specify Connection String

Source: https://www.gams.com/latest/docs/T_SQL2GMS.html

Example of providing a connection string via the command line.

```text
C="DSN=sample"
```

--------------------------------

### Matlab API - Control

Source: https://www.gams.com/latest/docs/apis/matlab_control/functions_q.html

Documentation for the GAMS Matlab API, including control functionalities, getting started guides, tutorials, and class references.

```APIDOC
## Matlab API - Control

### Description
Provides access to GAMS functionalities from Matlab, enabling control over GAMS execution and data transfer.

### Method
N/A (This is documentation, not an executable endpoint)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

## Matlab API - Class Reference

### Description
Detailed documentation for classes within the GAMS Matlab API.

### Method
N/A

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

## Class: QCP

### Description
Represents GAMS Options within the Matlab API.

### Class Members
- **QCP** : matlab.gams.control.Options
```

--------------------------------

### License Setup

Source: https://www.gams.com/latest/docs/S_MOSEK.html

Instructions for setting up a GAMS/MOSEK-Link license.

```APIDOC
# Setting up a GAMS/MOSEK-Link license

To use the GAMS/MOSEK solver with a GAMS/MOSEK-Link license you have save a MOSEK standalone license and point to the MOSEK license file via environment variable `MOSEKLM_LICENSE_FILE`.
```

--------------------------------

### Python API - Getting Started

Source: https://www.gams.com/latest/docs/apis/python/classgams_1_1control_1_1options_1_1HoldFixed.html

Information on getting started with the GAMS Python API.

```APIDOC
## Python API - Getting Started

### Description
This section provides guidance on how to begin using the GAMS Python API for model development and execution.
```

--------------------------------

### XPRESS Option File Example

Source: https://www.gams.com/latest/docs/S_XPRESS.html

An example of a solver-specific option file used to configure XPRESS parameters.

```text
   * sample XPRESS options file
   defaultalg 3
   presolve   0
   IterLim    50000
```

--------------------------------

### Python API - Getting Started

Source: https://www.gams.com/latest/docs/apis/python/classgams_1_1control_1_1options_1_1Filtered.html

Information on getting started with the GAMS Python API.

```APIDOC
## Python API - Getting Started

### Description
This section provides guidance on how to begin using the GAMS Python API for model execution and control.
```

--------------------------------

### Python API - Getting Started

Source: https://www.gams.com/latest/docs/apis/python/classgams_1_1control_1_1options_1_1ECLogLine.html

Information on getting started with the GAMS Python API.

```APIDOC
## Python API - Getting Started

This section covers the initial steps for using the GAMS Python API.

### Getting Started

*   Getting Started
```

--------------------------------

### Configure IPOPT Options in ipopt.opt

Source: https://www.gams.com/latest/docs/S_IPOPT.html

Create an `ipopt.opt` file to set IPOPT algorithm parameters. Each line should contain an option name, whitespace, and its value. Comments start with '#'.

```text
# This is a comment

# Turn off the NLP scaling
nlp_scaling_method none

# Change the initial barrier parameter
mu_init 1e-2

# Set the max number of iterations
max_iter 500

```

--------------------------------

### Get GAMS installation directory

Source: https://www.gams.com/latest/docs/apis/examples_java/Transport10_8java_source.html

Retrieves the installation directory of GAMS. Appends the file separator if it's not already present.

```java
String gamsdir = ws.systemDirectory();

if (!gamsdir.endsWith(GAMSGlobals.FILE_SEPARATOR))
    gamsdir += GAMSGLOBALS.FILE_SEPARATOR;
return gamsdir + "apifiles" + GAMSGLOBALS.FILE_SEPARATOR + "Data"
    + GAMSGLOBALS.FILE_SEPARATOR + "transport.xls";
```

--------------------------------

### Example of Listing Echo

Source: https://www.gams.com/latest/docs/UG_DollarControlOptions.html

Basic example of a set definition that would be echoed to the listing file.

```GAMS
Set i /0234*0237/
```

--------------------------------

### Example: SOLVE RESOURCE using MIP with GAMSCHK

Source: https://www.gams.com/latest/docs/S_GAMSCHK.html

This example illustrates setting GAMSCHK as the MIP solver and then solving the 'RESOURCE' model maximizing 'PROFIT'.

```gams
OPTION MIP=GAMSCHK;
SOLVE RESOURCE USING MIP MAXIMIZING PROFIT;
```

--------------------------------

### Include Headers for GAMS Example

Source: https://www.gams.com/latest/docs/apis/examples_cpp/transport4_8cpp.html

Include necessary headers for GAMS integration and standard C++ functionalities. This setup is required for the transport4 example.

```cpp
#include "gams.h"
#include <iostream>
#include <fstream>
#include <vector>
#include <map>
```

--------------------------------

### Full GAMS Embedded Code Example

Source: https://www.gams.com/latest/docs/T_LIBINCLUDE_PYEMBMI.html

A complete example demonstrating model setup, scenario data, and the embedded Python function for solving.

```GAMS
* GMSPYTHONLIB gets automatically set to use the internal Python installation in sysdir/GMSPython.
$if not setEnv GMSPYTHONLIB $abort.noError Embedded code Python not ready to be used
$log --- Using Python library %sysEnv.GMSPYTHONLIB%

Set
   i 'canning plants' / seattle,  san-diego /
   j 'markets'        / new-york, chicago, topeka /;

Parameter
   a(i) 'capacity of plant i in cases'
        / seattle    350
          san-diego  600 /

   b(j) 'demand at market j in cases'
        / new-york   325
          chicago    300
          topeka     275 /;

Table d(i,j) 'distance in thousands of miles'
              new-york  chicago  topeka
   seattle         2.5      1.7     1.8
   san-diego       2.5      1.8     1.4;

Scalar f 'freight in dollars per case per thousand miles' / 90 /;

Parameter c(i,j) 'transport cost in thousands of dollars per case';
c(i,j) = f*d(i,j)/1000;

Variable
   x(i,j) 'shipment quantities in cases'
   z      'total transportation costs in thousands of dollars';

Positive Variable x;

Equation
   cost      'define objective function'
   supply(i) 'observe supply limit at plant i'
   demand(j) 'satisfy demand at market j';

cost..      z =e= sum((i,j), c(i,j)*x(i,j));

supply(i).. sum(j, x(i,j)) =l= a(i);

demand(j).. sum(i, x(i,j)) =g= b(j);

Model transport / all /;

Set s 'scenarios to run' / base, run1, run2 /;

Table newsupply(s,i) 'updater for a (capacity)'
         seattle  san-diego
   base      350        600
   run1      300        650
   run2      400        550;

Table newdemand(s,j) 'updater for b (demand)'
         new-york  chicago  topeka
   base       325      300     275
   run1       325      300     275
   run2       350      300     250;

$set solverlog
$if set useSolverLog $set solverlog output=sys.stdout
embeddedCode Python:
def solveMI(mi, symIn=[], symOut=[]):
  for sym in symIn:
    gams.db[sym].copy_symbol(mi.sync_db[sym])
  mi.solve(%solverlog%)
  for sym in symOut:
    try:
      gams.db[sym].clear() # Explicitly clear the symbol to ensure setting "writtenTo" flag for sym
```

--------------------------------

### Configure SHOT options file

Source: https://www.gams.com/latest/docs/S_SHOT.html

Example content for a shot.opt file defining solver strategies and output settings.

```text
Dual.CutStrategy = 1
Dual.MIP.Solver = 2
Output.Console.DualSolver.Show = true
```

--------------------------------

### Example: SOLVE FEED using LP with GAMSCHK

Source: https://www.gams.com/latest/docs/S_GAMSCHK.html

This example shows setting GAMSCHK as the LP solver and then solving the 'FEED' model minimizing 'COST'.

```gams
OPTION LP=GAMSCHK;
SOLVE FEED USING LP MINIMIZING COST;
```

--------------------------------

### Test GAMS Installation via Terminal

Source: https://www.gams.com/latest/docs/UG_MAC_INSTALL.html

Execute these commands in the Terminal to verify your GAMS installation after setup. Ensure GAMS is added to your system's PATH.

```bash
gamslib trnsport
gams trnsport

```

--------------------------------

### GET getModelText

Source: https://www.gams.com/latest/docs/apis/examples_cpp/transport7_8cpp.html

Retrieves the GAMS model definition as a string for the transport7 example.

```APIDOC
## GET getModelText

### Description
Retrieves the GAMS model definition as a string, containing sets, parameters, variables, and equations for the transport7 model.

### Method
GET

### Response
#### Success Response (200)
- **model_string** (string) - The full GAMS model definition as a string.

#### Response Example
{
  "model_string": " Sets \n i canning plants / seattle, san-diego / \n j markets / new-york, chicago, topeka / ; ..."
}
```

--------------------------------

### Initialize Save/Restart Process

Source: https://www.gams.com/latest/docs/API_PY_CONTROL.html

Sets up the working directory and triggers the creation of the save/restart file.

```python
working_dir = os.path.join(os.curdir, "tmp")
create_save_restart(sys_dir, os.path.join(working_dir, "tbase"))
```

--------------------------------

### gmoGetMatrixCol

Source: https://www.gams.com/latest/docs/apis/expert-level/gmoqdrep.html

Get constraint matrix in column order with columns start only and NL indicator.

```APIDOC
## gmoGetMatrixCol

### Description
Get constraint matrix in column order with columns start only and NL indicator.

### Parameters
#### Path Parameters
- **colstart** (PLongIntArray) - Required - Index of Jacobian column starts with
- **rowidx** (PLongIntArray) - Required - Row index/indices of Jacobian
- **jacval** (PDoubleArray) - Required - Value(s) of Jacobian(s)
- **nlflag** (PLongIntArray) - Required - NL flag(s) of Jacobian(s) (0 : linear,!=0 : nonlinear)

### Response
- **Returns** (Integer)
```

--------------------------------

### Simple GAMS Server Implementation

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/annotated.html

Demonstrates how to implement a simple GAMS Server and Client. The example shows how to serialize GAMSJob components, send them to the server, and process the results.

```C#
/// <summary>
/// This example demonstrates how to implement a simple GAMS Server. The example has two parts: GAMSServer and GAMSClient. The example is configured to run the client and server on the same machine, but can easily be altered to run on different machines. Both client and server need access to the GAMSRemoteClass that implements the server. The method to communicate is very simple. The client sets up the ingredients for a GAMSJob (model text, GDX input, parameters) and sends them serialized (via a byte representation of the GDX and parameter file) to the server. The server recreates the GAMS objects from the serialized representations, runs the model, and ships GAMSJob.OutDB serialized back to the client for further processing
/// </summary>

```

--------------------------------

### GAMS Search Query Examples

Source: https://www.gams.com/latest/docs/apis/cpp/structgams_1_1GAMSOptions_1_1EForceWork-members.html

Examples of search queries for GAMS documentation, covering different categories like User's Guide, Solvers, Tools, APIs, and Release Notes.

```APIDOC
## GAMS Search Query Examples

### Description
Examples of how to use the search functionality to find specific GAMS resources.

### Query Examples
- **User's Guide**: `q=User's Guide`
- **Solvers**: `q=Solvers`
- **Tools**: `q=Tools`
- **APIs**: `q=APIs`
- **Release Notes**: `q=Release Notes`
- **Model Library**: `q=Model Library`
- **Test Data**: `q=Test Data`
- **EMP API**: `q=EMP API`
- **FIN NOA PSOPT**: `q=FIN NOA PSOPT`
```

--------------------------------

### Configure CBC Options File

Source: https://www.gams.com/latest/docs/S_CBC.html

Example content for a cbc.opt file to control solver behavior such as cut generation and perturbation settings.

```text
cuts root
perturbation off
```

--------------------------------

### Demo1GUI Program.cs Example

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/FarmGUI_2Program_8cs_source.html

Example C# code for the Program.cs file within the Demo1GUI project, demonstrating application entry point.

```APIDOC
## Program.cs (Demo1GUI)

### Description
This C# code defines the entry point for the Demo1GUI Windows Forms application.

### Method
`static void Main()`

### Endpoint
N/A

### Request Body
N/A

### Request Example
```csharp
using System;
using System.Collections.Generic;
using System.Linq;
using System.Windows.Forms;

namespace Demo1GUI
{
    static class Program
    {
        [STAThread]
        static void Main()
        {
            Application.EnableVisualStyles();
            Application.SetCompatibleTextRenderingDefault(false);
            Application.Run(new Form1());
        }
    }
}
```

### Response
N/A
```

--------------------------------

### Markowitz Portfolio Optimization Example

Source: https://www.gams.com/latest/docs/apis/examples_python/markowitz_8py.html

This example plots the efficient frontier for Markowitz's portfolio selection problem, optimizing for return and risk. It utilizes the GamsModelInstance class and requires the Python package matplotlib to be installed.

```Python
This is a small graphical program that plots the efficient frontier of Markowitz' portfolio selection problem with the two objectives return and risk. 
The example utilizes the GamsModelInstance class to solve the parameterized objective max lambda*return - (1-lambda)*risk in the most efficient way. This example requires the Python package matplotlib to be installed.
Definition in file markowitz.py.
```

--------------------------------

### Main function for Transport 10 example

Source: https://www.gams.com/latest/docs/apis/examples_cpp/transport10_8cpp.html

This is the main entry point for the Transport 10 example. It initializes the GAMS environment, loads data from Excel, sets up and solves a GAMS model, and prints the results. Ensure COM is initialized if using ActiveX.

```cpp
int main  | ( | int | _argc_ ,   
---|---|---|---
|  | char * | _argv_[] )  
166{
167 cout << "---------- Transport 10 --------------" << endl;
168 try {
169 ::CoInitialize(0); // initialize thread to use ActiveX (some systems may need CoInititializeEx)
170
171 GAMSWorkspaceInfo wsInfo;
172 if (argc > 1)
173 wsInfo.setSystemDirectory(argv[1]);
174 GAMSWorkspace ws(wsInfo);
175
176 // Creating the GAMSDatabase and fill with the workbook data
177 GAMSDatabase db = ws.addDatabase();
178 QString fileName = QString::fromStdString(ws.systemDirectory())+ cPathSep + "apifiles" + cPathSep + "Data" + cPathSep + "transport.xlsx";
179
180 QAxObject* excel = new QAxObject( "Excel.Application", 0 );
181 QAxObject* workbooks = excel->querySubObject( "Workbooks" );
182 QAxObject* workbook = workbooks->querySubObject( "Open(const QString&)", fileName );
183 QAxObject* sheets = workbook->querySubObject( "Worksheets" );
184
185 GAMSSet i = db.addSet("i", 1, "Plants");
186 GAMSSet j = db.addSet("j", 1, "Markets");
187
188 // read parameters
189 sheetToParameter(sheets, "capacity", db, "a", "Capacity", i);
190 sheetToParameter(sheets, "demand", db, "b", "Demand", j);
191 sheetToParameter(sheets, "distance", db, "d", "Distance", i, j);
192
193 // clean up and close up
194 workbook->dynamicCall("Close ()");
195 excel->dynamicCall("Quit ()");
196
197
198 // Create and run the GAMSJob
199 GAMSOptions opt = ws.addOptions();
200 GAMSJob t10 = ws.addJobFromString(getModelText());
201 opt.setDefine("gdxincname", db.name());
202 opt.setAllModelTypes("xpress");
203 t10.run(opt, db);
204 for (GAMSVariableRecord record : t10.outDB().getVariable("x"))
205 cout << "x(" << record.key(0) << "," << record.key(1) << "): level=" << record.level() <<
206 " marginal=" << record.marginal() << endl;
207
208 ::CoUninitialize();
209
210 } catch (GAMSException &ex) {
211 cout << "GAMSException occured: " << ex.what() << endl;
212 } catch (exception &ex) {
213 cout << ex.what() << endl;
214 }
215
216 return 0;
217}
```

--------------------------------

### Get Elapsed Time in GAMS

Source: https://www.gams.com/latest/docs/UG_Parameters.html

Returns the total time in seconds that has passed since the GAMS run started.

```gams
timeElapsed
```

--------------------------------

### Example: Using a Trigonometric Library

Source: https://www.gams.com/latest/docs/UG_ExtrinsicFunctions.html

This example demonstrates loading the 'tricclib' library with the internal name 'myLib' and declaring its 'Cosine', 'Sine', and 'Pi' functions. It then uses these declared functions to calculate and display a scalar value.

```gams
$funcLibIn myLib tricclib

Function myCos /myLib.Cosine/
         mySin /myLib.Sine/
         myPi  /myLib.Pi/;

Scalar d;
d = myCos(myPi/3);
display d;

```

--------------------------------

### Get Process ID of Last Job

Source: https://www.gams.com/latest/docs/UG_Parameters.html

Returns the process ID (PID) of the most recently started GAMS job.

```gams
jobHandle
```

--------------------------------

### Basic GUSS Scenario Setup

Source: https://www.gams.com/latest/docs/S_GUSS.html

Example of defining a GUSS dictionary to solve a DEA model across multiple scenarios.

```GAMS
Variable eff 'efficiency';


Equations defe    'efficiency definition - weighted output'
          denom   'weighted input'
          lime(i) 'output / input < 1';

defe..    eff =e= sum(jo, u(jo)*slice(jo));

denom..   sum(ji, v(ji)*slice(ji)) =e= 1;

lime(i).. sum(jo, u(jo)*data(i,jo)) =l= sum(ji, v(ji)*data(i,ji));

model dea /defe, denom, lime /;

set headers 'report' / modelstat, solvestat, objval /;
parameter scenrep(k,headers) 'solution report summary'
          scopt / SkipBaseCase 1 /;

set dict / k      .scenario.''
           slice  .param.   data
           eff    .level.   eff_k
           scopt  .opt.     scenrep /;

slice(j) = 0; option lp=cplex;
solve dea using lp max eff scenario dict;
display scenrep,eff_k;
```

--------------------------------

### Creating a solver option file

Source: https://www.gams.com/latest/docs/UG_Put.html

Example showing how to create and close a solver option file for MINOS.

```GAMS
File opt 'Minos option file'  / minos.opt /;
put opt 'Iteration limit          500'/
        'Feasibility tolerance    1.0E-7'/ ;
putclose opt;
```

```GAMS
putclose opt 'Iteration limit          500'/
             'Feasibility tolerance    1.0E-7'/ ;
```

--------------------------------

### C# .NET Control API Example: Tsp.cs

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/dir_4792ddf36049cb83fe2b5e7ad925b420.html

This C# code snippet is part of the .NET Control API examples, specifically demonstrating the Tsp (Traveling Salesperson Problem) functionality. It requires the GAMS .NET API to be installed and configured.

```csharp
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Gams
{
    public class Tsp
    {
        public Tsp()
        {
        }

        public void Run()
        {
            // TODO: Implement Tsp logic here
        }
    }
}
```

--------------------------------

### Verifying Gurobi license setup

Source: https://www.gams.com/latest/docs/S_GUROBI.html

Commands and expected output when solving a model to verify that the Gurobi license is correctly configured.

```bash
$ gamslib indus89
Copy ASCII : indus89.gms
$ gams indus89 lp gurobi
--- Job indus89 Start 09/01/20 12:41:41 32.2.0 rc62c018 LEX-LEG x86 64bit/Linux
[...]
Gurobi           32.2.0 rc62c018 Released Aug 26, 2020 LEG x86 64bit/Linux

Gurobi link license.
Gurobi library version 9.0.3
[...]
Iteration    Objective       Primal Inf.    Dual Inf.      Time
       0    7.1618935e+31   2.041808e+32   7.161894e+01      0s
    2990    1.1487366e+05   0.000000e+00   0.000000e+00      0s

Solved in 2990 iterations and 0.32 seconds
Optimal objective  1.148736556e+05

User-callback calls 3040, time in user-callback 0.00 sec
LP status(2): Model was solved to optimality (subject to tolerances).
--- Reading solution for model wsisn
*** Status: Normal completion
--- Job indus89.gms Stop 09/01/20 12:29:49 elapsed 0:00:00.835
```

--------------------------------

### Define an Ill-Defined MCP Model in GAMS

Source: https://www.gams.com/latest/docs/S_PATH.html

Example of a model where the function is undefined at the default starting point x=0, requiring an explicit initial value.

```GAMS
positive variable x;
equations F;

F.. 1 / x =g= 0;

model simple / F.x /;

x.l = 1e-6;

solve simple using mcp;
```

--------------------------------

### Display Initial Echo Print Listing

Source: https://www.gams.com/latest/docs/UG_GAMSOutput.html

Example of the initial compilation listing showing line numbers for empty lines and comments.

```text
A Quadratic Programming Model for Portfolio Analysis (ALAN,SEQ=124a)
C o m p i l a t i o n

   2
   4
      This is a mini mean-variance portfolio selection problem described in
      'GAMS/MINOS:Three examples' by Alan S. Manne, Department of Operations
       Research, Stanford University, May 1986.
  10
  11  * This model has been modified for use in the documentation
```

--------------------------------

### Get First GAMS Set Record

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/TestGAMSSymbol_8cs_source.html

Retrieves the first record of a GAMS set. This is commonly used as the starting point for iterating through the elements of a set.

```csharp
new GAMSSetRecord FirstRecord()
```

--------------------------------

### Execute GAMS C++ Example on Linux

Source: https://www.gams.com/latest/docs/API_CPP_TUTORIAL.html

Configures the library path and runs the transport1 example.

```bash
cd transport1
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<GAMS system directory>/apifiles/C++/lib
./transport1
```

--------------------------------

### Get First GAMS Parameter Record

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/TestGAMSSymbol_8cs_source.html

Retrieves the first record of a GAMS parameter. This is typically used as the starting point for iterating over parameter data.

```csharp
new GAMSParameterRecord FirstRecord()
```

--------------------------------

### Initialize and use a GAMSDatabase with GAMSJob

Source: https://www.gams.com/latest/docs/apis/dotnet/classGAMS_1_1GAMSDatabase.html

Demonstrates creating a database, defining it in GAMS options, and passing it to a GAMS job run.

```csharp
GAMSDatabase db = workspace.AddDatabase();
GAMSOptions opt = workspace.AddOptions();
opt.Defines.Add("SupplyDataFileName",db.Name);
...
gamsjob.Run(opt, db);
```

--------------------------------

### Get First GAMS Equation Record

Source: https://www.gams.com/latest/docs/apis/examples_dotnet/TestGAMSSymbol_8cs_source.html

Retrieves the first record associated with a GAMS equation. This is often used to start iterating through the records of an equation.

```csharp
new GAMSEquationRecord FirstRecord()
```

--------------------------------

### Rank Tool - Usage and Examples

Source: https://www.gams.com/latest/docs/T_ALG_RANK.html

Provides details on how to use the 'alg.Rank' tool via command line, compile time, and execution time, along with a practical example.

```APIDOC
## alg.Rank Tool

### Description
This tool sorts a one-dimensional symbol `sym` and stores the sorted indices in a one-dimensional parameter `symIdx`.

### Method
Command line, Compile time, or Execution time

### Endpoint
`gamstool [alg.]Rank sym symIdx gdxIn=fileIn.gdx gdxOut=fileOut.gdx` (Command line)
`$callTool [alg.]Rank sym symIdx [gdxIn=fileIn.gdx] [gdxOut=fileOut.gdx]` (Compile time)
`executeTool '[alg.]Rank sym symIdx [gdxIn=fileIn.gdx] [gdxOut=fileOut.gdx]'` (Execution time)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Arguments
- **sym** (string) - Required - Name of parameter or set to be sorted `sym(*)`
- **symIdx** (string) - Required - Name of parameter containing sort indexes `symIdx(*)`

### Named Parameters
- **gdxIn=fileIn.gdx** (string) - Optional - Name of GDX file that contains symbol sym. Mandatory if called from the command line, otherwise optional.
- **gdxOut=fileOut.gdx** (string) - Optional - Name of GDX file that contains symbol symIdx after execution. Mandatory if called from the command line, otherwise optional.

### Request Example
```
set I /i1 * i6/;
parameter A(I) /i1=+Inf, i2=-Inf, i3=Eps, i4= 10, i5=30, i6=20/;
parameter AIndex(i) 'permutation index';

* sort symbol; result in parameter AIndex
$callTool.checkErrorLevel 'alg.Rank A AIndex'
display AIndex;
```

### Response
#### Success Response (200)
Sorted indices are stored in the `symIdx` parameter.

#### Response Example
```json
{
  "AIndex": {
    "i1": 1,
    "i2": 2,
    "i3": 3,
    "i4": 4,
    "i5": 6,
    "i6": 5
  }
}
```

### Note
This tool is part of the GAMS Tools Library. Please inspect the general information about GAMS Tools. The complete example is also part of the GAMS Data Utilities Library, see model [GDXRANKExample18] for reference. The libInclude rank.gms uses this tool internally.
```

--------------------------------

### DICOPT Reading Option File Example

Source: https://www.gams.com/latest/docs/S_DICOPT.html

Illustrates the log messages when DICOPT reads an option file, showing the file being read and the start of the major iteration.

```text
  --- DICOPT: Reading option file D:\MODELS\SUPPORT\DICOPT.OPT
  > maxcycles 10
  --- DICOPT: Starting major iteration 1

```
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