Of course yes. It is possible to use several algorithms in different steps for solving a multi-objective problem. Whereas, the output of the first algorithm is considered the input for the following algorithm and so on. This process continues until the desired solution is obtained.

I think it's possible. combinatorial algorithms can be used to improve a single method and increase the possibility to generate optimum results. However, instead of combining two algorithms for two different methods (even it was mentioned one algorithm used as a constraint for others), It is essential to tune up the parameters of the algorithms for getting the optimum result. Also, consider also the computational time that will be increased since the algorithms are used sequentially.

Dear Benghelima Slimane Charafeddine,

I suggest you to see links on topic.

Book Emerging Trends in ICT for Sustainable Development

https://www.amazon.com/Evolutionary-Computation-Combinatorial-Optimization-Proceedings/dp/3540786031

Article Dynamic Lexicographic Approach for Heuristic Multi-objective...

Article Multi-Objective Sustainable Truck Scheduling in a Rail–Road ...

Best regards

You most certainly can. In fact, there may be an advantage in employing such a method since we know that some algorithms are better suited for some problems over others (NFL theorem). Just be sure to properly select the correct MH for any given objective function. This may require some experimentation on your part, but whatever you do, don't let the algorithm selection process be randomized. A methodological approach needs to be adopted here.

Personally, I would advise using Pareto-based techniques instead of conventional non-Pareto-based approaches like Lexicographic or weighted sum optimization. Nonetheless, good luck!