This paper considers simulation of truck dispatching system designs using maximum expected production of the truck-shovel system as the measure of perfommnce. Two methods are utilized, multiple comparisons with the best (MCB) and the combination of MCB and the variance reduction technique known as common random numbers (CRN). These two techniques are compared via simulation experiments.The results show that the combined procedure of MCB with CRN is the superior tool to reduce the total number of replications needed to ensure the specified probability of correct selection over the finite number of designing systems.In this case study, MCB with CRN reduces the variance by 29°/0 and the number of required replications by 48Y0. Also, the MCB with CRN procedure narrowed the confidence interval by 18°/0.
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.
The power plant owner is interested to know in advance the quality of coal to be burnt which should meet maximal efficiency of power plant and the environmental regulations. There is the need to control and to predict the quality of coal at the mine site to meet sulfur emission requirements. Coal quality control between the mine site and the utility plant is a complex problem owing to the variable nature of coal properties (heating value, sulfur, ash), even within the same coal seam. Due to the fluctuation of the coal quality, mine planning and coal homogenization are in fact an optimization problem under uncertain conditions. To deal with these issues a stochastic optimization model is developed for an illustrative coal homogenization problem. Mining block grades from an optimized mining schedule are used to simulate any given homogenization process in stockpiles throughout the mine's life. Sulfur content is treated as lognormally distributed random variable. The objectives of the model include minimizing the expected sulfur content and standard deviation in sulfur content. The methodology was illustrated using the case study on Kolubara surface coal mine.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.