1. Rade Biočanin, Srpska kraljevska akademija inovacionih nauka (SKAIN) Beograd, Serbia
2. Jovan Vasilijević, Srpska kraljevska akademija inovacionih nauka (SKAIN) Beograd, Serbia
The expansion of e-commerce and the globalization of logistical chains have led to a drastic increase in the frequency of undeclared and hidden hazardous materials within standard postal and transport flows, posing a severe threat to ecological safety, public health, and ecosystem stability. The clearly defined objective of this co-authored paper is to establish an innovative, hybrid multi-criteria optimization (MCO) model that integrates the AHP and TOPSIS mathematical methods with artificial intelligence (AI) algorithms, enabling predictive risk identification and dynamic routing of transport vehicles carrying hazardous cargo.
Transport and storage of dangerous goods (ADR) involves strictly regulated handling of substances that can endanger human health and the environment. In our region, the Law on the Transport of Dangerous Goods is applied, harmonized with the international ADR agreement, which includes certified packaging, trained drivers, proper marking of vehicles and special storage conditions to prevent accidents. Considering the repectiveness of this academy and scientific gathering, this work requires the highest level of methodological rigor, precise terminology (especially in the field of transportation of dangerous shipments, eco-security and postal technologies) and a clear contribution to applied artificial intelligence. This paper presents a comprehensive scientific and professional study focused on solving critical challenges in the management of dangerous goods within postal systems. Beyond technical and technological aspects, this paper affirms a broader humanistic approach, according to which the awareness of negative anthropogenic impacts on the planet implies a responsibility to rectify these processes through new management systems. By addressing the critical issue of nuclear, chemical, and biological (CBRN) accidents in postal networks, the proposed model contributes to the fundamental structural changes necessary for implementing the concept of sustainable development, ensuring ecosystem protection for both present and future generations. Special emphasis in the paper is placed on operational experience from the domain of chemical, biological, radiological, and nuclear (CBRN) defense in preventing hazardous accidents. The empirical part of the research was conducted through a structured survey questionnaire consisting of 6 thematic blocks on a representative sample of 180 respondents from the fields of logistics, defense, and ecology. The data processing results confirm that the application of the proposed MCO-AI model enables a transition from a reactive to a predictive ecological defense system, minimizing risks to the population and natural resources while maintaining the economic sustainability of transport and the principles of sustainable development.
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Datum:
11.08.2026.
Contemporary Materials 2026 - Savremeni Materijali
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(3.67 MB)
