Abstract: Solving constrained multi-objective optimization problems (CMOPs) involves simultaneously achieving convergence to the Pareto front, preserving solution diversity, and satisfying complex ...

The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been investigated for years. In a recent breakthrough published in the Chinese Journal of ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

School of Information Engineering, Qujing Normal University, Qujing, China. Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this ...

Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...

Abstract: Evolutionary Algorithms (EAs) are effective for solving Multi-Modal Multi-Objective Optimization Problems which optimal solutions subsets distributed regularly in the decision space.

The urban low-altitude logistics network adopts a hub-and-spoke, multi-layered structure. Its nodes are waypoints mapped to corresponding altitude layers based on spoke nodes (delivery spots) and hub ...