A memorized multi-objective Sinh-Cosh optimizer for solving multi-objective engineering design problems.

ABSTRACT: The Multi-Objective Sinh-Cosh Optimization Algorithm (MOSCHO) is presented in this article based on the memorized technique. MOSCHO is an extension version of the recently proposed Sinh-Cosh optimizer for multiple objective optimizations. The memorized local optimum is integrated with the global optimal solution to bound the search space and update positions of solutions for obtaining non-dominated solutions. The proposed method is tested on mathematical non-constrained functions, SRN constrained function, and three real-world design engineering applications, as a vital challenge to handle the difficulties of real-world engineering applications. The MOSCHO's performance was evaluated by seven performance metrics compared to some of the most popular multi-objective optimization algorithms.

SUBMITTER: El-Nagar D 

PROVIDER: S-EPMC12827340 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature