OPTIMIZATION OF THE CUSTOMS INSPECTION SYSTEM USING SIMULATION MODELING UNDER RESOURCE CONSTRAINTS

Abstract

Relevance of the study is determined by the increasing intensity of international transport flows, growing complexity of logistics chains, and stricter requirements for customs security under persistent constraints of human, technical, and time resources at border crossing points. Under these conditions, traditional approaches to organizing customs inspections prove insufficient, as they fail to adequately account for the stochastic nature of transport flows, nonlinear congestion effects, and the need to balance inspection speed with control depth. This substantiates the necessity of applying quantitative and simulation-based methods to support evidence-based managerial decisions. The aim of the article is to optimize the customs inspection system through the application of simulation modeling of transport flows under resource constraints in order to achieve a balanced ratio between the speed of customs procedures and the effectiveness of detecting customs violations. Research methods are based on discrete-event simulation modeling implemented in Simul8 and Arena environments, the Monte Carlo method to account for stochastic uncertainty, sensitivity analysis to identify critical system parameters, and elements of multi-criteria optimization. Customs inspection processes are represented as a queuing system with limited resources and variable flow intensity. Research results demonstrate that the customs inspection system should be interpreted as a nonlinear stochastic system in which throughput capacity and inspection effectiveness are in a conflicting relationship. Threshold values of transport flow intensity and resource availability have been identified, beyond which inspection time increases sharply while the probability of detecting violations declines. It has been proven that flexible allocation of human and technical resources yields higher efficiency than extensive intensification of control measures, while excessive inspection rigor exhibits a saturation effect. The conclusions summarize that simulation modeling provides a scientifically sound tool for optimizing customs inspection in conditions of uncertainty and limited resources. The feasibility of using an optimization model for selecting management decisions to maintain a stable balance between the speed of customs clearance and customs security has been proven.Prospects for further research may be related to the integration of real-time data, the development of adaptive risk-oriented algorithms, and the introduction of digital decision support systems into the activities of customs authorities.