Border surveillance optimization using a multi-objective mathematical model

Abstract

The potential danger of illegal cross-border activities has raised international concern over enhanced border security. In the context of sustainable development for a border security system, it has been identified the need to better understand it, evaluate its capabilities and identify the key trade-offs between different elements. Recalling the complexity of border surveillance subsystem, which is generated by the diversity and high number of illegal cross-border activities that should be detected at land border, a high number of resources and technologies are needed. Optimal surveillance solution to help preventing and deterring illegal activities along land borders are required. Considering the interdependent performances for border surveillance subsystem, the paper presents a mathematical framework to support the selection of surveillance solutions at land border. Specifically, the paper describes how the multi-objective optimization problem of choosing surveillance solutions can be solved using a dedicated multi-criteria tool.