The strategic planning of open-pit mining projects is highly influenced by geological variability, economic fluctuations, and operational uncertainties. Traditional deterministic optimization models often fail to account for these uncertainties, leading to potentially misleading economic evaluations. This paper proposes a hybrid model that integrates deterministic and stochastic optimization methods, following the principles of the ISO 31000 risk management framework, to comprehensively quantify uncertainty through key parameters affecting strategic mine planning. Monte Carlo simulations were applied to generate probability distributions of input parameters, including metal prices, mining and processing costs, and ore grade variability, allowing for a more robust financial assessment. The results demonstrate that while the deterministic approach estimates an NPV of USD 130.8 million, the stochastic model yields an average NPV of USD 155.5 million with a standard deviation of USD 76.5 million, highlighting the significant variability in financial outcomes. Risk assessment using Value at Risk (VaR) and Conditional Value at Risk (CVaR) further quantifies potential financial losses, revealing a 3% probability of project unprofitability. The developed methodology provides a structured approach to integrating uncertainty into mine planning, enabling more reliable economic evaluations and improving decision-making in strategic mining operations.

Purpose: This paper aims to develop a system, which would enable efficient management and exploitation of documentation in electronic form, related to mining projects, with information retrieval and information extraction (IE) features, using various language resources and natural language processing. Design/methodology/approach: The system is designed to integrate textual, lexical, semantic and terminological resources, enabling advanced document search and extraction of information. These resources are integrated with a set of Web services and applications, for different user profiles and use-cases. Findings: The use of the system is illustrated by examples demonstrating keyword search supported by Web query expansion services, search based on regular expressions, corpus search based on local grammars, followed by extraction of information based on this search and finally, search with lexical masks using domain and semantic markers. Originality/value: The presented system is the first software solution for implementation of human language technology in management of documentation from the mining engineering domain, but it is also applicable to other engineering and non-engineering domains. The system is independent of the type of alphabet (Cyrillic and Latin), which makes it applicable to other languages of the Balkan region related to Serbian, and its support for morphological dictionaries can be applied in most morphologically complex languages, such as Slavic languages. Significant search improvements and the efficiency of IE are based on semantic networks and terminology dictionaries, with the support of local grammars.