Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) have demonstrated strong performance in solving low- and medium-dimensional expensive multi-objective optimization problems (EMOPs).
A review of over 500 reports of cannibalistic behavior in snakes finds it's appeared multiple times in different evolutionary lineages, leading researchers to hypothesize it's beneficial for snakes ...
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 ...
ABSTRACT: Visual Sensor Networks (VSNs) focus on capturing data, extracting relevant information, and enabling communication. However, the presence of obstacles affects network efficiency, linking ...
Abstract: Evolutionary Algorithms (EAs) are effective for solving Multi-Modal Multi-Objective Optimization Problems which optimal solutions subsets distributed regularly in the decision space.
This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...
With the increase of the scale of the micro-grid system, the optimization of microgrid power dispatching becomes a challenging issue. From the perspective of algorithm design, traditional heuristic ...
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