Hybrid scalarization technique for solving multiobjective quadratically constrained quadratic programming

In this paper, the Hybrid scalarization technique is exploited for solving multiobjective quadratically constrained quadratic programming problems with (non)convex quadratic function. To this end, a linear programming relaxation is derived that computes a lower bound on the optimal objective value of the scalarization problem. Basically, the proposed algorithm aims to find efficient solutions to the problem by solving the linear relaxation sequentially on the subsets of the feasible region.