Discrete Event Simulation for Intelligent Supply Chains: A Data-Driven Systematic and Bibliometric Review

Maidana-Aquino G.; Valenzuela-Galván J.; Gamboa-Cruzado J.; García C.E.J.; Delgado F.D.C.; Carhuamaca A.D.; Meza Á.N.; Chanona-Hernández L. · Computacion y Sistemas (2026) · DOI: 10.13053/cys-30-1-6343

Resumen

The increasing complexity of supply chains has driven the adoption of computational approaches such as discrete-event simulation (DES) to optimize logistics processes, reduce costs, and enhance decision-making. This paper presents a systematic and bibliometric literature review aimed at analyzing the most relevant scientific contributions regarding the application of DES in supply chain management. A rigorous methodology was employed, based on the PRISMA 2020 flow and Kitchenham's approach, selecting 64 papers published between 2018 and 2024 from databases including Scopus, IEEE Xplore, ACM, ARDI, and ScienceDirect. The findings were organized around five research questions. Key criteria such as flexibility, accuracy, and adaptability were identified to assess the effectiveness of simulation models (RQ1). Regarding supply chain management, the most commonly used indicators were demand, costs, and inventory (RQ2). Additionally, a significant proportion of the papers were published in Q1 and non-quartile journals, indicating both thematic consolidation and expansion (RQ3). Co-occurrence networks reflected the leadership of countries like the United States and China (RQ4). Finally, the most frequently addressed topics were risk management, integrated logistics, and data modeling (RQ5), revealing both mature areas and others still under development.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional Daniel Alcides Carrión; Universidad Nacional Federico Villarreal; Universidad Nacional de Cañete; Universidad Nacional de Moquegua