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Setting Up a Batch Environment

Recall that the first step in building an optimization model is to create a Gurobi environment. An environment provides a number of configuration options; among them is an option to indicate where the model should be solved. You can solve a model locally, on a Compute Server, or using a Gurobi Instant Cloud server. If you have a Cluster Manager installed, you also have the option of using batch optimization.

To use batch optimization, you should configure your environment as if you will be using a Compute Server through a Cluster Manager. You'll need to set the CSManager parameter to point to your Cluster Manager, and provide a valid UserName and ServerPassword. The difference is that you will also need to set the CSBatchMode parameter to 1. This will cause the client to build the model locally, and only submit it to the server once a call to the optimizeBatch method is made. This is in contrast to a standard Compute Server job, where the connection to the server is established immediately and the model is actually built on the server.

The following shows how you might set up your environment for batch optimization (in Python):

    env = gp.Env(empty=True)
    env.setParam('LogFile',        'batchmode.log')
    env.setParam('CSManager',      'http://localhost:61080')
    env.setParam('UserName',       'gurobi')
    env.setParam('ServerPassword', 'pass')
    env.setParam('CSBatchMode',    1)

Note that you can also use CSAPIAccessID and CSAPISecret (instead of UserName and ServerPassword) to connect to a Cluster Manager.

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Next: Tagging Variables or Constraints Up: Batch Optimization Previous: Batch Optimization