I want to solve a Mixed Integer problem with several constraints. Gurobi or Google OR tools solve such problems. Though I am not sure, I think they use an exact method such as branch and bound or plane cut. Whereas, OptaPlanner is a metaheuristic solver. Does it give equally good results in terms of optimality?
Gurobi, Google OR-Tools, and OptaPlanner are all powerful optimization solvers, but they differ in terms of the techniques they employ and the types of problems they are best suited for. Let's discuss their approaches and the trade-offs between optimality and efficiency.
When comparing the optimality of solutions, exact methods like Gurobi and OR-Tools generally provide provably optimal solutions if given sufficient runtime. On the other hand, metaheuristics like OptaPlanner may not always guarantee optimality but can often provide good solutions within practical time constraints.
The choice between Gurobi/Google OR-Tools and OptaPlanner depends on your specific problem characteristics, time constraints, and the importance of achieving optimality. If optimality is critical and the problem size is manageable, Gurobi or OR-Tools may be preferable. However, if scalability, efficiency, and a good-quality solution within a reasonable time frame are more important, OptaPlanner's metaheuristic approach can be a viable choice.
It's worth noting that different solvers may perform differently on specific problem instances, so it's beneficial to experiment and compare their results on your particular problem to determine the most suitable solver for your needs.
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