Artículo

Unveiling the Potential of Metaheuristics in Transportation: A Path Towards Efficiency, Optimization, and Intelligent Management

Resumen

Importance: This bibliometric analysis of the application of metaheuristics in transportation and logistics examines over two decades of research (1999–present), aiming to uncover global trends, anticipate future directions, and highlight how interconnections between key factors facilitate the development of practical and sustainable solutions for the industry. Methodology: A quantitative approach is employed to analyze the evolution of the discipline by reviewing an extensive database of relevant research and key authors and utilizing advanced data processing tools. This analysis enables the assessment of advances in the optimization of metaheuristic models, with an impact on time and cost savings from an economically sustainable perspective. Results: The use of metaheuristics optimizes the efficiency and competitiveness of the transportation sector while promoting a positive economic impact on companies. The main areas of application are optimization and metaheuristic methods, cost and operational efficiency, planning and scheduling, logistics and transportation, supply chain and logistics networks, energy and sustainability, and demand and users. Additionally, genetic algorithms stand out as particularly important. Conclusions: This research provides a comprehensive and detailed view of the impact of metaheuristics on the transportation sector, highlighting their current and future trends (such as artificial intelligence) and their economic relevance.
Zeng, Lin (59304657200); Shi, Yihan (59304657100); Subatijang, Parhati (59350252900); Zhang, Lei (59350368800); Gao, Jian (59276502500); Sun, Rongxin (56574635100); Jiang, Kan (57370621600)
Global research trends and hotspots in rheumatoid arthritis joint replacement:Bibliometric analysis and visualization study
2025
10.1016/j.jor.2024.09.017
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205361667&doi=10.1016%2fj.jor.2024.09.017&partnerID=40&md5=4229a5e01e71046df9b23673cd8f5a62
Affiliated to the Sixth Affiliated Hospital of Xinjiang Medical University, China
All Open Access
Scopus
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