biostudies-literatureUnknownAqel IThe COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constraints. The problem is solved by resorting to three nature-inspired algorithms of artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping algorithm (SFLA), and adaptive particle swarm optimization (ADAP-PSO). A penalty function is implemented to handle the constraints and the results obtained are compared.<h4>Supplementary information</h4>The online version contains supplementary material available at 10.1007/s12008-023-01256-1.International journal on interactive design and manufacturing1-10https://www.ebi.ac.uk/biostudies/studies/S-EPMC9975440biostudies-literatureOptimal reliability allocation of heterogeneous components in pharmaceutical production plant.PMC9975440Mellal MAAqel IfalseOptimal reliability allocation of heterogeneous components in pharmaceutical production plant.The COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constraints. The problem is solved by resorting to three nature-inspired algorithms of artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping algorithm (SFLA), and adaptive particle swarm optimization (ADAP-PSO). A penalty function is implemented to handle the constraints and the results obtained are compared.<h4>Supplementary information</h4>The online version contains supplementary material available at 10.1007/s12008-023-01256-1.2023-01-01T00:00:00Z2023 Mar2026-05-29T21:08:48.078Z2025-04-05T13:02:41.181ZS-EPMC99754404047946710.1007/s12008-023-01256-1