{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T22:40:58Z","timestamp":1776120058916,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T00:00:00Z","timestamp":1583280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>In this paper, we develop and apply a genetic algorithm to solve surgery scheduling cases in a Mexican Public Hospital. Here, one of the most challenging issues is to process containers with heterogeneous capacity. Many scheduling problems do not share this restriction; because of this reason, we developed and implemented a strategy for the processing of heterogeneous containers in the genetic algorithm. The final product was named \u201cgenetic algorithm for scheduling optimization\u201d (GAfSO). The results of GAfSO were tested with real data of a local hospital. Said hospital assigns different operational time to the operating rooms throughout the week. Also, the computational complexity of GAfSO is analyzed. Results show that GAfSO can assign the corresponding capacity to the operating rooms while optimizing their use.<\/jats:p>","DOI":"10.3390\/axioms9010027","type":"journal-article","created":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T10:46:08Z","timestamp":1583318768000},"page":"27","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Genetic Algorithm for Scheduling Optimization Considering Heterogeneous Containers: A Real-World Case Study"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2365-4651","authenticated-orcid":false,"given":"Gilberto","family":"Rivera","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Autonomous University of Cd. Ju\u00e1rez, Cd. Ju\u00e1rez 32315, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Cisneros","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Autonomous University of Cd. Ju\u00e1rez, Cd. Ju\u00e1rez 32315, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5514-5061","authenticated-orcid":false,"given":"Patricia","family":"S\u00e1nchez-Sol\u00eds","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Autonomous University of Cd. Ju\u00e1rez, Cd. Ju\u00e1rez 32315, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nelson","family":"Rangel-Valdez","sequence":"additional","affiliation":[{"name":"Postgraduate &amp; Research Division, National Mexican Institute of Technology\/Madero Institute of Technology, Cd. Madero, Tamaulipas 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6588-8336","authenticated-orcid":false,"given":"Jorge","family":"Rodas-Osollo","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Autonomous University of Cd. Ju\u00e1rez, Cd. Ju\u00e1rez 32315, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,4]]},"reference":[{"key":"ref_1","unstructured":"Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Professional."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Agarwal, M., and Srivastava, G.M.S. (2016, January 29\u201330). A Genetic Algorithm Inspired Task Scheduling in Cloud Computing. 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