I am learning about the GRASP (Greedy Randomized Adaptive Search) meta-heuristics.
From what I understood, GRASP is based on two main phases. The first one:
Construct a initial solution based on a greedy and random strategy
and the second one:
Construct a local search on the previous found solution
The question that I have is for the first phase. Do I have to create a feasible solution?
Am I allowed maybe to create an infeasible solution in the first phase of the algorithm, and then use local search to find a feasible solution?
EDIT:
Basically I have the Weighted Partial Max SAT problem. The idea is that I have to maximize the sum of all the satisfied soft clauses, while at the same time satisfying all hard clauses.
What I was thinking is to create an initial solution (maybe infeasible) that tries to maximize the number of satisfied soft clauses. After that I want to use a local search to optimize the solution even more, or make it feasible if necessary.
I want to know if that is a valid strategy, because the initial construction may create an infeasible solution.
