To address these challenges, we propose a novel dynamic multiobjective particle swarm optimization approach with cooperative agents. In this strategy, the ...
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Dynamic Multi-objective optimization problems (DMOPs) involve multiple objectives, constraints, and parameters that may change over time.
The proposed CPSO uses cooperative behavior among multiple subswarms to decompose the neural fuzzy systems into rule-based subswarms, and each particle within ...
Thus, we propose a new cooperative particle swarm optimization with a reference-point-based prediction strategy to solve DMOPs. In the proposed method, multiple ...
This method allocates a dynamic number of sub-population as required to improve diversity in the search space. Additionally, agents are used for better ...
Jan 27, 2019 · Abstract:This paper investigates a new hybridization of multi-objective particle swarm optimization (MOPSO) and cooperative agents ...
Dynamic Multi-objective Optimization problems (DMOPs) involve multiple objectives, constraints, and parameters that may change over time.
This method allocates a dynamic number of sub-population as required to improve diversity in the search space. Additionally, agents are used for better ...
This paper investigates a new hybridization of multi-objective particle swarm optimization and cooperative agents (MOPSO-CA) to handle the problem of ...
To tackle this issue, this paper proposes a novel algorithm, termed: Many- Objective PSO with Cooperative Agents (MaOPSO-CA). This exploits an Inverted ...