{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Aqel I"],"pubmed_abstract":["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."],"journal":["International journal on interactive design and manufacturing"],"pagination":["1-10"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9975440"],"repository":["biostudies-literature"],"pubmed_title":["Optimal reliability allocation of heterogeneous components in pharmaceutical production plant."],"pmcid":["PMC9975440"],"pubmed_authors":["Mellal MA","Aqel I"],"additional_accession":[]},"is_claimable":false,"name":"Optimal reliability allocation of heterogeneous components in pharmaceutical production plant.","description":"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.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Mar","modification":"2026-05-29T21:08:48.078Z","creation":"2025-04-05T13:02:41.181Z"},"accession":"S-EPMC9975440","cross_references":{"pubmed":["40479467"],"doi":["10.1007/s12008-023-01256-1"]}}