Metaheuristiques/README.md
2021-04-06 12:09:56 +02:00

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# Heuristic methods for JobShop scheduling
This repository contains the starter code for the assignment.
## Working in IntelliJ
For working on this project, we recommend using the IntelliJ-IDEA development environment. It is available in INSA's
classrooms as well as on `montp.insa-toulouse.fr`.
To import the project in IntelliJ (once IntelliJ is running):
- Open a new project : `Open project` or `File > Open`
- Select the `gradle.build` file in the cloned repository.
- Select `Open as project`.
To run the program in IntelliJ, you can
- Right click on the `src/main/java/Jobshop/Main` class in the project view.
- Select `Run Main.main()`. It should complain that some arguments are missing.
- Give it the expected command line arguments : `Run > Edit Configuration`, then fill in the `Program arguments` text box.
## Working on the command line (Gradle)
Compilation instructions are given for Linux. On Windows you can use the `gradlew.bat` script (but you are on your own).
```
./gradlew build # Compiles the project
```
The project can be executed directly with `gradle` by specifying the arguments like so :
```
./gradlew run --args="--solver basic random --instance aaa1 ft"
```
You can also build an executable jar file, and run it with the java command.
This is especially useful if you want to run it on another machine.
```
# Create a jar file with all dependencies in build/libs/JSP.jar
./gradlew jar
# Run the jar file. Only requires a Java Runtime Environment (JRE)
java -jar build/libs/JSP.jar --solver basic --instance ft06
```
The command line above indicates that we want to solve the instance named`ft06` with the `basic` solver. It should give an output like the following :
```
basic
instance size best runtime makespan ecart
ft06 6x6 55 1 60 9.1
AVG - - 1.0 - 9.1
```
Fields in the result view are the following :
- `instance`: name of the instance
- `size`: size of the instance `{num-jobs}x{num-tasks}`
- `best`: best known resultfor this instance
- `runtime`: time taken by the solver in milliseconds (rounded)
- `makespan`: makespan of the solution
- `ecart`: normalized distance to the best result: `100 * (makespan - best) / best`
One can also specify multiple solvers (below `basic` and `random`) and instances (below `ft06`, `ft10` and `ft20`) for simultaneous testing:
```
java -jar build/libs/JSP.jar --solver basic random --instance ft06 ft10 ft20
basic random
instance size best runtime makespan ecart runtime makespan ecart
ft06 6x6 55 1 60 9.1 999 55 0.0
ft10 10x10 930 0 1319 41.8 999 1209 30.0
ft20 20x5 1165 0 1672 43.5 999 1529 31.2
AVG - - 0.3 - 31.5 999.0 - 20.4
```
Here the last line give the average `runtime` and `ecart` for each solver.
```
sage: jsp-solver [-h] [-t TIMEOUT] --solver SOLVER [SOLVER ...]
--instance INSTANCE [INSTANCE ...]
Solves jobshop problems.
named arguments:
-h, --help show this help message and exit
-t TIMEOUT, --timeout TIMEOUT
Solver timeout in seconds for each instance.
(default: 1)
--solver SOLVER [SOLVER ...]
Solver(s) to use (space separated if more than
one)
--instance INSTANCE [INSTANCE ...]
Instance(s) to solve (space separated if more
than one). All instances starting with the given
String will be selected. (e.g. "ft" will select
the instances ft06, ft10 and ft20.
```
## IDE Support
Most IDEs should provide support for importing gradle projects. However, our experience has been best with IntelliJ so far and we would recommend it.
#### IntelliJ
IntelliJ has worked best, with out of the box support for the import of gradle projets:
https://www.jetbrains.com/help/idea/gradle.html#gradle_import_project_start
#### Eclipse
Most technical problems have been related to the use of Eclipse so we don't recommend using it unless you have a good reason to.
We have however configured gradle to allow generating an eclipse configuration like so :
```
./gradlew eclipseClean eclipse
```