Dynamic multi-objective optimization problems (DMOPs) are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the proposal of ...

In this paper, a framework of neurodynamic system consisting of two subsystems with different time-scale is firstly developed for solving multi-objective convex optimization problems. By designing a ...

Tan Liu, Qinyun Yuan, Lina Wang, Yonggang Wang, Nannan Zhang, Multi-objective optimization for oil-gas production process based on compensation model of comprehensive energy consumption using improved ...

In this paper, we aim to find ecient solutions of a multi-objective optimization problem over a linear matrix inequality (LMI in short), in which the objective functions are SOS-convex polynomials. We ...

Abstract: This study contributes a many-objective analysis of water supply in the Tarrant Regional Water District (TRWD) in Texas in the United States, in order to demonstrate how multiobjective ...

Multi-Objective Particle Swarm Optimization (MOPSO) and the Multi-Objective Covariance Matrix Adaptation Evolution Strategy (MO-CMA-ES) apply swarm intelligence and probabilistic modeling, ...

Considering the multi-objective trade-off and synergy of groundwater level decline, dietary energy, economic benefits, vitamin C and feed output, they put forward the optimization solutions for ...