# How to reduce workload

Redistricting Optimization is NP-Hard Computation. The more polygons (or the more nodes in the polygons), the heavier the computation. There are several ways to reduce the workload and calculation time.

## Simplify the data

Simplify the polygon can reduce the data size and therefore reduce the workloads. iRedistrict doesn't provide the function to simplify polygons. QGIS can be used to do the simplification. QGIS is free: <https://www.qgis.org/>

## Use cluster to reduce workloads

The clustering function can produce a number of clusters to replace the original units. For example, produce 1000 clusters for 10K units, can reduce the number of polygons from 10K to 1K. Usually, if the data size is larger than&#x20;

![](/files/-MJdrLiUxxVBQLAaTCdZ)

## Use COI to reduce the workloads

COI groups units into one larger area. It helps to reduce the number of polygons and reduce the workloads.&#x20;

##


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://zillion.gitbook.io/iredistrict/tip-how-to-reduce-workload.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.