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Learn about different local search meta-heuristics: To develop intuition for creating a solver configuration that utilizes different local search meta-heuristics in Optaplanner, you need to first familiarize yourself with the different local search meta-heuristics available in Optaplanner. Some examples include tabu search, simulated annealing, and late acceptance.

Understand how each meta-heuristic works: After you have learned about the different local search meta-heuristics in Optaplanner, you need to understand how each meta-heuristic works. This will help you determine which meta-heuristic is best suited for solving a particular optimization problem.

Determine the specific optimization problem you are trying to solve: Before you can start creating a solver configuration, you need to determine the specific optimization problem you are trying to solve. This will help you determine which meta-heuristics are suitable for solving the problem.

Create a solver configuration: Once you have determined the optimization problem you are trying to solve and which local search meta-heuristics are suitable, you can start creating a solver configuration. This involves specifying the meta-heuristics to use, their parameters, and other solver-related properties.

Test and refine the solver configuration: After you have created the solver configuration, you need to test it on different optimization problems and refine it based on the results. This will help you identify areas where your solver configuration can be improved.

Keep learning: Finally, it is important to continually learn about new meta-heuristics and their applications in optimization problems. This will help you develop intuition for creating solver configurations that are more effective at solving different types of optimization problems.