Solving the Flow-Shop Schedulling problem with Ant Colony Optimization algorithms.
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README.md

aco-flowshop

A Java Program to solve the Flow-Shop Scheduling Problem using Ant Colony Algorithms. The implemented method is based on the paper "An ant approach to the flow shop problem" by Thomas Stutzle.

The Ant-Colony Algorithm

The Ant Colony algorithm used to solve the problem is based on Max-Min Ant System. To implement it, we used the Isula Framework:

      ProblemConfiguration configurationProvider = new ProblemConfiguration(problemRepresentation);
      AntColony<Integer, FlowShopEnvironment> colony = getAntColony(configurationProvider);
      FlowShopEnvironment environment = new FlowShopEnvironment(problemRepresentation);
      configurationProvider.setEnvironment(environment);

      AcoProblemSolver<Integer, FlowShopEnvironment> solver = new AcoProblemSolver<>();
      solver.initialize(environment, colony, configurationProvider);

      solver.addDaemonActions(
              new StartPheromoneMatrix<Integer, FlowShopEnvironment>(),
              new FlowShopUpdatePheromoneMatrix());
      solver.getAntColony().addAntPolicies(
              new PseudoRandomNodeSelection<Integer, FlowShopEnvironment>(),
              new ApplyLocalSearch());

      solver.solveProblem();

The implemented process has the following characteristics:

  • We have specialized Ants that build possible solutions while traversing the problem graph. The quality of each solution is expressed by its makespan.
  • After an Ant has built a solution, a Local Search Procedure is used to improve its quality. This is accomplished through the Daemon Action ApplyLocalSearch.
  • The procedure used by an Ant to add another component to its solution is the Pseudo-Random rule proposed in the Ant Colony System algorithm. This algorithm used the policy implementation provided by the framework in the class PseudoRandomNodeSelection.
  • As we're working with the Max-Min Ant System algorithm, we need to follow its rules regarding pheromone update. For that, we use the Pheromone Initialization Policy available on the Framework on StartPheromoneMatrix, and extend the Update Policy to suit the needs of our problem.

The results

This program generates a graphical representation of the best solution found:

Flow Shop Scheduling Solution

How to use this code

The code uploaded to this GitHub Repository corresponds to a Maven Java Project. As such, it is strongly recommended that you have Maven installed before working with it.

This project depends on the Isula Framework. You need to download and install the Isula Framework Project on your local Maven repository. Follow the instructions available in https://github.com/cptanalatriste/isula

Keep in mind that several file and folder locations were configured on the ProblemConfiguration.java file. You need to set values according to your environment in order to avoid a FileNotFoundException. Once this is ready, you can launch this project by executing mvn exec:java -Dexec.mainClass="pe.edu.pucp.ia.aco.AcoFlowShopWithIsula" from the project root folder.

More about Isula

Visit the Isula Framework site: http://cptanalatriste.github.io/isula/

Review the Isula JavaDoc: http://cptanalatriste.github.io/isula/doc/

Questions, issues or support?

Feel free to contact me at carlos.gavidia@pucp.edu.pe.