[wenc]

> What I meant is that in the case if your problem is formulated in a way that the CPLEX and Gurobi cannot treat it (e.g., stochastic and multiobjective) and is not very large-scale, then one can use heuristics. However, the efficiency of the latter will likely depend on hyperparameter settings which need to be set properly.

Ah makes sense... stochastic and multiobjective formulations have superstructures that are not exploited by MIP solvers by default, so hyperparameter tuning might be useful. Creating (exact) heuristics for these superstructures are also an active area of research.

Some solvers like CPLEX are starting to natively support higher level structures like Benders decompositions [1], but they will never support every structural variation.

[1] Benders: https://www.ibm.com/support/knowledgecenter/en/SSSA5P_12.7.0...