Arslan HilalUğurlu OnurEliiyi Deniz Türsel2023-03-222023-03-22202225097873https://doi.org/10.1007/978-981-16-8997-0_12https://hdl.handle.net/20.500.14034/842Bio-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.eninfo:eu-repo/semantics/closedAccessArtificial Bee ColonyArtificial intelligenceBio-inspired algorithmsCuckoo SearchEvolutionary algorithmsFinancial prediction and planningFirefly algorithmMetaheuristicsPortfolio optimizationSwarm intelligenceBook Chapter10.1007/978-981-16-8997-0_122072242-s2.0-85130834357N/A