Abstract: Differential evolution exhibits strong performance in real parameter single objective optimization. Ensemble of similar differential evolution algorithms has been proposed in literature.

Abstract: Learning differential evolution (DE) algorithms are widely adopted to address flexible job-shop scheduling problems (FJSPs) because of the optimization ability. However, traditional learning ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

2D irregular shape bin-cutting with heterogenous bins using evolutionary metaheuristics, Particle Swarm Optimization (PSO) and Differential Evolution (DEGL). In python, using shapely. The ...

ABSTRACT: The African continent remains the least electrified, particularly acute in sub-Saharan Africa, where there is a significant gap between urban and rural electrification rates. To address the ...

📌 ClusterDEBO: A Cluster-Assisted Differential Evolution-Based Hybrid Oversampling Algorithm This Python implementation provides ClusterDEBO, a hybrid oversampling method designed to address class ...

In recent years, due to rapid fossil fuel depletion (Peng et al., 2020), booming global energy demand (Shangguan et al., 2020a), and a series of severe eco-environmental problems (Yang et al., 2015), ...

The radiative transfer phenomenon is modeled by an integro-differential equation known as Boltzmann equation. This equation describes mathematically the interaction of the radiation with the ...