Aqel, IbrahimMellal, Mohamed Arezki2023-03-202023-03-20202319552513https://link.springer.com/article/10.1007/s12008-023-01256-1DOI 10.1007/s12008-023-01256-1https://dspace.univ-boumerdes.dz/handle/123456789/11214he 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 comparedenCOVID-19Grey wolf optimizer-shuffled frog-leaping algorithm-adaptive particle swarm optimizationHeterogeneous componentsPharmaceutical plantReliability allocationArticle