# Schedule Optimization

# 1. Consider your real production

In the early years of the project you will find a lot of concerns and the most value in terms of NPV. Knowing that, we decide to consider a **10-year surface to optimize the first 5 years**. By an obvious assumption, as the surface used corresponds to a decade, it will contain the interval from the 1st to 5th period and represents a lot more mass. However, this simple input can restrict the space where the algorithm has to find a solution which **could reduce the run time **and **help it to deliver better results** respecting the set of constraints given.

Example:

Processing capacity: 10 Mt per year.

Total movement: 40 Mt per year.

Maximum of 4,000 processing hours in 5 years.

Vertical rate of advance as 150m per year.

Minimum Mining (50 m) and Bottom(100 m) width.

Restrict Mining Surface: Surface002 from

*Exploratory Analysis*.Grade copper until 0.7%.

Stockpiling parameters on.

## 1.1 Comparing Results

Notice that by running the scenario Exploratory Analysis, which corresponds to a 5-year package, we could just reach 44.6 Mt of production although there was a capacity of 50Mt. The aspect which caught our attention is that the** processing hours constraint** was in **its limits**, which probably is the** main variable interfering in the processing capacity. **

By running scenario * Schedule Optimization*, in a yearly bases guided by that corresponds to a 10-year period, the firsts 5 years achieved 48.8 Mt respecting the set of constraints. Therefore, by using this **efficient workflow to focus on the most important periods** we could **reduce the runtime** to take decisions and **enhance our whole reporting with this data.**

Considering this example we start to understand how can we optimize better the initial periods of our projects. You can also** limitate your schedule with surfaces from step ****Best Case**** ****if more efficiency is needed.** This multi-period optimization could take longer, so itβs also recommended to be** run in a powerful machine**, in parallel, while other tests are performed. Another useful tip is to **add constraints gradually** this run so that we can identify conflicts among them and/or bottlenecks. At the next step, we start to refine our results, since we already have a broader view we can decide which way you should attempts can we try to solve the challenges of the project.