The Differential Evolution (DE) has stood as a cornerstone of Evolutionary Computation (EC), inspiring numerous approaches. Despite its foundational role, the selection stage of DE has received little attention, with only 2% of documented modifications in the literature on this aspect. Recent research has underscored the potential for significant algorithmic improvement through thoughtful modifications to this critical stage, particularly in accelerating the exploitation phase. This study introduces a novel EC strategy rooted in DE principles. To enhance algorithmic exploration, a systematic decision-making process regarding function evaluations is employed to select between two of the most... More >

Farmers sometimes grow crops with low yields, wasting land, labor, and time—especially in developing countries where demand for food is increasing. A Crop Recommendation System (CRS) can help by using precision farming techniques that analyze soil and environmental data to suggest the most suitable crops. This study proposes a CRS using a Modified Salp Swarm Algorithm (MSSA) for feature selection and an Adaptive Weighted Bi-directional Long Short-Term Memory (AWBiLSTM) ensemble for prediction. MSSA enhances the original algorithm by improving local search and convergence speed, addressing SSA’s limitations. Climate data is pre-processed and relevant features are selected using MSSA. AWBi... More >

The IECE Transactions on Swarm and Evolutionary Learning (TSEL) is a new journal focused on nature-inspired computation. This journal is launched at a time when swarm and evolutionary algorithms have impacted different areas of research. Their progress is not only theoretical but also applications in complex tasks, supporting their adaptability and popularity. In this sense, TSEL aims to be at the forefront of the rapidly evolving landscape of these interdisciplinary fields. On behalf of the editorial team, I warmly welcome scholars, experts, researchers, and readers who support and follow our journal. More >