MiningMath

MiningMath

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Unlimited scenarios and decision trees for your strategic evaluations

Evaluating constraints

Estimated reading: 2 minutes 178 views

MiningMath has a flexible mining optimization algorithm that consists of a Mixed Integer Linear Programming (MILP) formulation and linearization methods that tackle the challenging non-linear aspects of the problem. It is the only mining package able to handle a diverse range of constraints in a single-step process. However, such range of available constraints raises the question: 

How to add all the required constraints without losing too much value?

There is no exact procedure, as each constraint models a different engineering aspect. Therefore, there must be an experienced engineer willing to explore a range of possibilities by building Decision Trees, wisely choosing scenarios that get closer to the real problem (more constraints added) without losing so much value (or even gaining, given some non-linear aspects).

The following sections suggest possible workflows that can be followed in order to perform an efficient analysis.

Initial analysis

It is important to analyze scenarios to measure the impact of each constraint on the project’s net present value (NPV), from the Super Best Case to a detailed setup. For example, with a NPV Upside Portential analysis.

When performing such an evaluation it is common that the cumulative NPV usually decreases (as expected) when more constraints are added. However, there are exceptions as described in the following section.

Non-linear constraints

Geometric constraints are modelled as non-linear restrictions. This non-linearity can lead to counterintuitive results, with more constraints potentially causing a better NPV. Hence, if you are not happy with the results achieved after adding geometric constraints you might need to perform a Selectivity Analysis or Best-Worst Range Analysis of your project.

Other workflows

MiningMath offers a diverse range of Workflows that can be followed in order to improve your project’s results. If you are still struggling with certain parameters or constraints, please have a look on all possible options to identify what would be better suited to your particular case.

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