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
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
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)