Abstract: Dynamic constrained multi-objective optimization problems are characterized by time-varying objectives, decision variables, and constraints, presenting significant challenges for ...
Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.
Abstract: Constrained multi-objective optimization problems (CMOPs) are of great significance in the context of practical applications, ranging from scientific to engineering domains. Most existing ...