"reformulation-and-linearization"

like in 2019:

https://www.researchgate.net/post/How_can_I_linearize_the_product_of_two_variables

or in:

https://www.researchgate.net/post/Do_you_know_some_feasible_methods_to_reformulate_a_mixed-integer_bilinear_programming_model_into_a_mixed-integer_linear_programming_MILP_model

or simply using available solvers like 2021

https://www.researchgate.net/post/What_solver_do_you_recommend_to_solve_bilinear_matrix_inequality_BMI_problems

or 2018

https://www.researchgate.net/post/Is-there-any-free-SDP-solver-for-bilinear-matrix-inequalities-constraints

... good luck

Constraint handling is not necessarily an integral component of a specific metaheuristic but rather a general technique that can be incorporated into any algorithm, including metaheuristics, to address constraints effectively. There are various strategies to handle non-linear equality constraints, such as penalty functions, repair methods, decoders, or multi-objective approaches, which can be adapted based on the problem context and the chosen algorithm.

For a deeper understanding of how to handle constraints in optimization, I recommend reviewing the following papers: