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We propose two different frameworks for planning capacity decisions and present a two-stage stochastic model for each one of them. While in the first model decisions related to capacity scalability are modeled as first-stage decisions, in the second model, capacity adjustments are deferred to the second stage. We develop the extensive forms of the associated stochastic programs for the case of demand uncertainty being captured by a finite set of scenarios. Additional inequalities are proposed to enhance the original formulations. An extensive computational study with randomly generated instances shows that the proposed enhancements are very useful. Specifically, 97.5% of the instances can be solved to optimality in much shorter computing times. Important insights are also provided into the impact of the two different frameworks for planning capacity adjustments on the facility network configuration and its total cost.<\/jats:p>","DOI":"10.1007\/s40314-021-01560-0","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T07:02:37Z","timestamp":1624604557000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Integrated facility location and capacity planning under uncertainty"],"prefix":"10.1007","volume":"40","author":[{"given":"Isabel","family":"Correia","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1412-0807","authenticated-orcid":false,"given":"Teresa","family":"Melo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"1560_CR1","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1057\/palgrave.jors.2601834","volume":"56","author":"E Aghezzaf","year":"2005","unstructured":"Aghezzaf E (2005) Capacity planning and warehouse location in supply chains with uncertain demands. 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