Abstract
Electromagnetism-like Mechanism (EM) is a population based optimization approach, which has been recently adapted to solve multiobjective (MO) problems (MOEM). In this work, an enhanced multiobjective Electromagnetism-like Mechanism algorithm is proposed (EMOEM). To assess this new algorithm, a comparison with MOEM algorithm is performed. Our aim is to assess the ability of both algorithms in a wide range of continuous optimization problems including benchmark problems with two and three objective functions. Experiments show that EMOEM performs better in terms of convergence and diversity when compared with the MOEM algorithm.
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Carrasqueira, P., Alves, M.J., Antunes, C.H. (2014). An Improved Multiobjective Electromagnetism-like Mechanism Algorithm. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_51
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DOI: https://doi.org/10.1007/978-3-662-45523-4_51
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