Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization.

ABSTRACT: Bi-objective optimization problems arise when a process needs to be optimized with respect to two conflicting objectives. Solving such problems produces a set of points called the Pareto front, where no objective can be improved without worsening at least one other objective. Existing deterministic methods for solving Multi-Objective Optimization Problems (MOOPs) include scalarization techniques, which transform the problem into a set of Single-Objective Optimization Problems (SOOPs) where each of them is to be solved independently to obtain a point on the Pareto front. In this paper, we propose an alternative strategy that tackles bi-objective optimization problems by exploring the objective space recursively at a reduced computational cost. Our approach is inspired by how plants efficien

SUBMITTER: Hashem I 

PROVIDER: S-EPMC12316258 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature