Are Genetic Algorithm (GA) tools capable of solving GIS based problems?

By definition, Genetic Algorithm is very easy to explain i.e. it mimics the original process which is occurring in nature so that we can get a better and robust solution which satisfies the fitness criteria by combining the optimal combinations of things which is a repetitive process. Let us take an example, it can be applied to the financial market in terms of price to earnings ratio. It is a better indicator of future conditions because the market is fluctuating every second. Some good strategy might work today but might not work tomorrow.

I think everyone gets a basic idea about Genetic Algorithm but definitely everyone gets an hiccup when it comes to using it in our problem to get effective results. Here I will constrict my discussion to GIS or more sharply we can say especially related to spatially based problems.


It is an inevitable fact that GIS is the emerging future. Using Genetic Algorithms can change the face of GIS world. So we can use Genetic Algorithms as a DSS (Decision Support System) in various GIS field such as in:-

  1. Land management by effective planning or improving agricultural efficiency in terms of shape, size and value.
  2. Highway alignment for connecting end points which helps us to reduce the overall cost.
  3. Cartography for resolve the spatial conflict between the object while scaling the map as we know that while scaling some objects becomes fuzzy so we can miss it out our important feature due to the overlapping or stretch in size.fractal-art-995167_1280
  4. Image segmentation while processing the difficult techniques such as object recognition, feature extraction etc.

Software Availabe

Now there are some softwares which process GIS based problems related to Genetic Algorithm such as:-

  • GA Lib (MATLab) (COTS)
  • GALib (C++) (OpenSource)
  • Python (OpenSource)
  • R (OpenSource)
  • Genetic Line Simplifier plugin in QGIS (OpenSource)
  • Weka (OpenSource)
  • Rapidminer (OpenSource)


At the end we can conclude that GIS and Genetic Algorithm integration will solve the complex problems very easily with flexibilty that also helps the decision maker’s. In my upcoming post, I will focus on how to use this algorithm in available software.

Please share your views and comments on this to enrich and help other readers.

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[…] Genetic algorithms are used now a days for solving problems with optimal outputs. Its integration with GIS can help to solve problems regarding distribution of various kinds of facilities over a region with respect to certain fitness functions. GIS is the smart solution for developing a city. It may take all required consideration i.e. area, distance slope, etc. which is primary data used to develop any area or city. GIS can also provide both 2D and 3D views of features which can help in decision making and better visualization for future development. Read more about Genetic Algorithm tools for solving GIS… Read more »
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