3 papers
cs.NE2025
Enhancing Decision Space Diversity in Multi-Objective Evolutionary Optimization for the Diet Problem
Gustavo V. Nascimento, Ivan R. Meneghini, Valéria Santos +2
Multi-objective evolutionary algorithms (MOEAs) are essential for solving complex optimization problems, such as the diet problem, where balancing conflicting objectives, like cost…
math.OC2025
Maximum Dispersion, Maximum Concentration: Enhancing the Quality of MOP Solutions
Gladston Moreira, Ivan Meneghini, Elizabeth Wanner
Multi-objective optimization problems (MOPs) often require a trade-off between conflicting objectives, maximizing diversity and convergence in the objective space. This study prese…
cs.CL2025
MOPrompt: Multi-objective Semantic Evolution for Prompt Optimization
Sara Câmara, Eduardo Luz, Valéria Carvalho +2
Prompt engineering is crucial for unlocking the potential of Large Language Models (LLMs). Still, since manual prompt design is often complex, non-intuitive, and time-consuming, au…