There is a Gurobi video Faster MIPs Using Custom Heuristics
MIPs often solve faster with good integer feasible solutions. Thus,
Gurobi contains a variety of MIP heuristics to create integer
solutions and improve them. However, sometimes you can improve upon
this with custom integer heuristics that exploit model structure.
In this webinar, you will learn:
What models may benefit from custom MIP heuristics, and how to build
your own custom MIP heuristics by using the traveling salesman problem
to illustrate different integer heuristics that take advantage of both
model structure and relaxed solution values in the MIP tree.
Without going custom, the amount of time the Gurobi solver devotes to feasibility heuristics can be controlled by the Heuristics parameter.
Heuristics Time spent in feasibility heuristics Type: double
Default value: 0.05 Minimum value: 0 Maximum value: 1
Determines the amount of time spent in MIP heuristics. You can think
of the value as the desired fraction of total MIP runtime devoted to
heuristics (so by default, we aim to spend 5% of runtime on
heuristics). Larger values produce more and better feasible solutions,
at a cost of slower progress in the best bound.
Note: Only affects mixed integer programming (MIP) models