Abstract: Most existing constrained multi-objective evolutionary algorithms primarily rely on heuristic search and empirically designed operators, often overlooking the underlying causal relationships ...
Abstract: Solving constrained multi-objective optimization problems (CMOPs) involves simultaneously achieving convergence to the Pareto front, preserving solution diversity, and satisfying complex ...
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 ...
Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this study, we investigate the case of multi-attraction tourism planning in Qujing ...
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