Strategic Decision-Making in SMEs : A Review of Heuristics and Machine Learning for Multi-Objective Optimization
Molina-Abril, Gines (Universitat Oberta de Catalunya-)
Calvet Liñan, Laura (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Juan, Ángel A (Universitat Politècnica de València)
Riera Terrén, Daniel (Universitat Oberta de Catalunya)

Data:	2025
Resum:	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' 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.
Ajuts:	Agencia Estatal de Investigación PID2022-138860NB-I00 Agencia Estatal de Investigación RED2022-134703-T
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article de revisió ; recerca ; Versió publicada
Matèria:	Heuristics ; Machine learning ; Strategic decision-making ; Optimization ; Small and medium enterprises
Publicat a:	Computation (Basel), Vol. 13, Núm. 7 (July 2025) , art. 173, ISSN 2079-3197

DOI: 10.3390/computation13070173

22 p, 523.8 KB

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