{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T02:00:56Z","timestamp":1781920856372,"version":"3.54.5"},"reference-count":113,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science and the Spanish Research Agency","award":["PID2022- 138860NB-I00"],"award-info":[{"award-number":["PID2022- 138860NB-I00"]}]},{"name":"Spanish Ministry of Science and the Spanish Research Agency","award":["RED2022-134703-T"],"award-info":[{"award-number":["RED2022-134703-T"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>Small- and medium-sized enterprises (SMEs) face dynamic and competitive environments where resilience and data-driven decision-making are critical. Despite the potential benefits of artificial intelligence (AI), machine learning (ML), and optimization techniques, SMEs often struggle to adopt these tools due to high costs, limited training, and restricted hardware access. This study reviews how SMEs can employ heuristics, metaheuristics, ML, and hybrid approaches to support strategic decisions under uncertainty and resource constraints. Using bibliometric mapping with UMAP and BERTopic, 82 key works are identified and clustered into 11 thematic areas. From this, the study develops a practical framework for implementing and evaluating optimization strategies tailored to SMEs\u2019 limitations. The results highlight critical application areas, adoption barriers, and success factors, showing that heuristics and hybrid methods are especially effective for multi-objective optimization with lower computational demands. The study also outlines research gaps and proposes future directions to foster digital transformation in SMEs. Unlike prior reviews focused on specific industries or methods, this work offers a cross-sectoral perspective, emphasizing how these technologies can strengthen SME resilience and strategic planning.<\/jats:p>","DOI":"10.3390\/computation13070173","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T10:10:38Z","timestamp":1752833438000},"page":"173","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Strategic Decision-Making in SMEs: A Review of Heuristics and Machine Learning for Multi-Objective Optimization"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7877-0812","authenticated-orcid":false,"given":"Gines","family":"Molina-Abril","sequence":"first","affiliation":[{"name":"Department of Computer Science, Multimedia, and Telecommunication, Open University of Catalonia, 08018 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8425-1381","authenticated-orcid":false,"given":"Laura","family":"Calvet","sequence":"additional","affiliation":[{"name":"Telecommunications and Systems Engineering Department, Universitat Aut\u00f2noma de Barcelona, 08202 Sabadell, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1392-1776","authenticated-orcid":false,"given":"Angel A.","family":"Juan","sequence":"additional","affiliation":[{"name":"Research Centre on Production Management and Engineering, Universitat Polit\u00e8cnica de Val\u00e8ncia, 03801 Alcoy, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4718-7234","authenticated-orcid":false,"given":"Daniel","family":"Riera","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Multimedia, and Telecommunication, Open University of Catalonia, 08018 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bianchini, M., and Sancho, M.L. 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