Hierarchical Model
Hierarchical Model Results
The graphical and numerical summary of the percentages obtained for prioritization is shown below.
Final weights of the Hierarchical Model
Once the decisions are analyzed from the hierarchical decomposition, the AHP manages to combine all the judgments, therefore deducing the weights that reflect the Perceptions and values proposed by each of the participants. It’s important not to lose at any time, sight of the general objective and the interdependencies existing between the sets of factors, criteria and alternatives.
If we put all the variables weights and criteria together a final value is obtained, the general objective, which will be the data that will allow us to perform the prioritization of the deposits.
Through the percentages calculated with the AHP and a scale of values assigned to each one of the priorization fields, with a range between 0 and 1 based on their higher or smaller affection in the deposits valorization, it is possible to obtain a ranking based on their potential to held an exploitation.
To do this, each percentage of the alternatives is multiplied by the value assigned to these fields, after which a weighted sum of the values obtained in each criterion based on the percentage or weight assigned to them within the 100% corresponding to the final objective.
The table below shows the ranking obtained at the end of the complete prioritization process.
Comparison between two prospect
To make a brief and simplified example of how the ranking works, the first and last ranks have been compared to see how variations in characteristics affects.
In the first position of the ranking created appears Huequi the deposit belongs to the X region and in the last one appears Estero Limávida which belongs to the VII region. These two deposits meet the following characteristics:
Facing the different characteristics of each prospect, it can be easily understood the reason for its position. Starting with the criteria referring to the business potential:
• It is observed that in Huequi the mineral is distributed throughout the whole column which a priori indicates that it is a deposit in which all the material will be treated. So, there will be no difference between sterile and mineral.
• Regarding the remaining fields Huequi is superior in both volume and total mineralization potential.
In terms of economic and technical feasibility criteria:
• Both share the type of prospect, current terraces.
• In the rest of the fields, Huequi again has better weighted characteristics when it comes to valuing the prospect. As explained in previous points the proximity of water and the appearance of boulders and clay are decisive points when making a project of these characteristics.
• On the other hand, the type of gold that is in Huequi offers better characteristics for its treatment. The gold in the Estero Limávida is the most difficult to process. Therefore, the one with the highest punishment within the model.
Other operating variables:
• As for land use, Estero Limávida may find it difficult to get permission because it is an agricultural area, while in Huequi it’s easier to get permission in the area.
• On the other hand, none of the prospects has protected areas, so the difference in this subcriteria is not relevant.
•For both, climate and water availability, the balance is in favor of Huequi due to its geographical location as it is in the X region.
• Regarding to the nearby communities, one has and the other does not, but this does not offer much difference. It may be preferable one or the other option, depending on the way of proceeding or manager’s decision.
Business impact:
• The unemployment rate is higher in Limávida estuary, this variable does not have a specific weight that high in the model. So, it is not as influential when it comes to building up the ranking.
All characteristics are turned into numerical data based on the scales explained throughout the report. By means of the calculated percentages of influence of each criterion using the AHP model they end up giving rise to a single numerical indicator used to rank the prospects. The result obtained by these two deposits was 0.86 for Huequi and 0.31 for estero Limávida.
To test the sensitivity of the model, expert’s priorities were weighed by varying their importance compared to the other participants in the prioritization workshop. Varying expert’s weight based on their area of higher knowledge, it was concluded that the model was consistent since the ranking remained practically equal applying large changes in each expert’s priority.
