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Genetic Algorithms for Go/Golang

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14 reviews
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4.1
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Genetic Algorithms for Go/Golang Reviews

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PULKIT D.
PD
PULKIT D.
07/04/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Reusability of Code is smooth

Alterations of code is a cake walk, with this platform. And since it is an open source product by GitHub one can easily reuse the code available and implement it. Another appreciating element is the deeply descriptive documentation it provides, this makes things easier even for beginners.
VC
Virginia C.
07/01/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Genetic Algorithms for Go/Golang pros and cons

I like how it is an open-source code that you can get in GitHub with complete documentation. It is suitable for solving optimization issues and could also be used in images.
Mamata K.
MK
Mamata K.
10+ years of experience in Web Development | Project Leader | Team Player | CSM | Oracle | Postgres
05/27/2023
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Good optimisation techniques

First of all it is open source and available on GitHub, which make it easier to use and adapt. It is very useful when dealing with complex optimization problems. Support parallel programming as well as can handle a wide range of problem types and constraints.

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What is Genetic Algorithms for Go/Golang?

Genetic Algorithms for Go/Golang, accessible at [https://github.com/thoj/go-galib](https://github.com/thoj/go-galib), is a library that implements genetic algorithms in the Go programming language. This library is suitable for developers looking to solve optimization and search problems using genetic algorithm techniques. It provides functionalities to create populations, evolve them through generations, and apply selection, crossover, and mutation operations to optimize solutions iteratively. The library is designed to be flexible, allowing users to customize components of the genetic algorithm to fit their specific problem requirements.

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Website
github.com