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    An overview of new generation bio-inspired algorithms for portfolio optimization
    (Springer, 2022) Arslan Hilal; Uğurlu Onur; Eliiyi Deniz Türsel
    Bio-inspired computing is one of the foremost subfields of artificial intelligence, which aims to tackle complex optimization problems. The main advantage of bio-inspired algorithms over traditional methods is their searching ability. Portfolio selection is a popular optimization problem in economics and finance. It aims to find an optimal allocation of capital among a set of assets by maximization of return with simultaneous minimization of risk. Since the portfolio optimization problem is NP-hard, a large number of researchers have resorted to bio-inspired algorithms to deal with the computational complexity. This study provides an overview of the new generation bio-inspired algorithms from the recently published literature for portfolio optimization. Besides, opportunities for future research within this area discussed. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.