GeneticAlgorithm | Here I give an introduction to Genetic Algorithms My videos

 by   nsadawi Java Version: Current License: No License

kandi X-RAY | GeneticAlgorithm Summary

kandi X-RAY | GeneticAlgorithm Summary

GeneticAlgorithm is a Java library typically used in Video applications. GeneticAlgorithm has no vulnerabilities and it has low support. However GeneticAlgorithm has 6 bugs and it build file is not available. You can download it from GitHub.


            kandi-support Support

              GeneticAlgorithm has a low active ecosystem.
              It has 26 star(s) with 21 fork(s). There are 7 watchers for this library.
              It had no major release in the last 6 months.
              GeneticAlgorithm has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of GeneticAlgorithm is current.

            kandi-Quality Quality

              GeneticAlgorithm has 6 bugs (0 blocker, 4 critical, 0 major, 2 minor) and 83 code smells.

            kandi-Security Security

              GeneticAlgorithm has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              GeneticAlgorithm code analysis shows 0 unresolved vulnerabilities.
              There are 4 security hotspots that need review.

            kandi-License License

              GeneticAlgorithm does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              GeneticAlgorithm releases are not available. You will need to build from source code and install.
              GeneticAlgorithm has no build file. You will be need to create the build yourself to build the component from source.
              GeneticAlgorithm saves you 260 person hours of effort in developing the same functionality from scratch.
              It has 630 lines of code, 46 functions and 6 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed GeneticAlgorithm and discovered the below as its top functions. This is intended to give you an instant insight into GeneticAlgorithm implemented functionality, and help decide if they suit your requirements.
            • Runs the GA
            • Inserts an int array
            • Evolves a population over the population
            • Method to perform an Order1 crossover on two int arrays
            • Find the nearest points in two line segments
            • Find the Euclidean distance between two points
            • Returns the minimum element of a double array
            • Prints the members of the population
            • Swaps the elements of an array
            • Used for testing
            • Method to mutate an int array
            Get all kandi verified functions for this library.

            GeneticAlgorithm Key Features

            No Key Features are available at this moment for GeneticAlgorithm.

            GeneticAlgorithm Examples and Code Snippets

            No Code Snippets are available at this moment for GeneticAlgorithm.

            Community Discussions


            parallel stream function taking more time
            Asked 2021-Mar-28 at 08:34

            I have the following function which is calculating the fitness of each individual in Genetic algorithm. Fitness function is taking very much time so that for each individual in population, it is taking a whole lot of time.



            Answered 2021-Mar-28 at 06:06

            If you take a long time to getFitness(), you should minimize its call.



            Tail Recursive Genetic Algorithm throwing "AWT-EventQueue-0" java.lang.StackOverflowError
            Asked 2020-Jul-17 at 11:18

            I have created a project that runs a genetic algorithm to solve a maze, the optimal chromosome is calculated using a tail recursive function to prevent a StackOverflowError.

            The error produced by the console is:



            Answered 2020-Jul-17 at 11:18

            Java does not implement the tail recursion optimisation: Tail Call Optimisation in Java You have to replace the recursion with a loop manually. Luckily it's easy:



            ValueError: Found input variables with inconsistent numbers of samples: [2839, 14195]
            Asked 2020-May-12 at 23:14

            before this dataset all the previous ones worked fine, now with this new dataset it rais the below errors, I tried to reshape the X_train but it is not attributed for X_trian, anyone can help. thank you



            Answered 2020-May-12 at 23:14

            Given that 14916 / 5 is 2839, I'm assuming that the cause of your issue is that you have more than one output label (5 labels) and you're using .ravel()

            This will flatten your data and the model will think you're trying to pass in # of labels * number_of_training_examples examples as your training examples.

            To fix this, instead of using .ravel() you should reshape your final y_train so it has a shape of number_of_training_examples x number_of_labels



            C - Genetic Algorithm for N Queens
            Asked 2020-Apr-25 at 07:08

            I'm trying to figure our how to use the Genetic Algorithm to solve N queens.

            Here is the program:



            Answered 2017-Mar-30 at 10:24

            Not sure if this is the cause of your specific issue, but it is a problem:



            What is a good way of telling low level objects which factories to use?
            Asked 2019-Dec-18 at 07:14

            I've been learning a lot about Design Patterns lately, specifically Dependency Injection. I'm pretty sure that abstract factorys are a good way of instantiating objects that have dependencies. However I'm not sure how to tell lower level objects what factories they are supposed to use.

            Consider following simplified example:

            I have a class MainProgram (I just made this to represent that there is other code in my program..) At some point during runtime I want to instantiate a IGeneticAlgorithm with an abstract factory:



            Answered 2019-Dec-18 at 07:14

            When it comes to using Dependency Injection, the Abstract Factory pattern is often over-used. This doesn't mean that it's a bad pattern per se, but in many cases there are more suitable alternatives for the Abstract Factory pattern. This is described in detail in Dependency Injection Principles, Practices, and Patterns (paragraph 6.2) where is described that:

            • Abstract Factories should not be used to create short-lived, stateful dependencies, since a consumer of a dependency should be oblivious to its lifetime; from perspective of the consumer, there should conceptually be only one instance of a service.
            • Abstract Factories are often Dependency Inversion Principle (DIP) violations, because their design often doesn't suit the consumer, while the DIP states: "the abstracts are owned by the upper/policy layers", meaning that consumer of the abstraction should dictate its shape and define the abstraction in a way that suits its needs the most. Letting the consumer depend on both a factory dependency and the dependency it produces complicates the consumer.

            This means that:

            • Abstract Factories with a parameterless create method should be prevented, because it implies the dependency is short-lived and its lifetime is controlled by the consumer. Instead, Abstract Factories should be created for dependencies that conceptually require runtime data (provided by the consumer) to be created.
            • But even in case a factory method contains parameters, care must be taken to make sure that the Abstract Factory is really required. The Proxy pattern is often (but not always) better suited, because it allows the consumer to have a single dependency, instead of depending on both the factory and its product.

            Dependency Injection promotes composition of classes in the start-up path of the application, a concept the book refers to as the Composition Root. The Composition Root is a location close to that application's entry point (your Main method) and it knows about every other module in the system.

            Because the Composition Root takes a dependency on all other modules in the system, it typically makes little sense consume Abstract Factories within the Composition Root. For instance, in case you defined an IXFactory abstraction to produce IX dependencies, but the Composition Root is the sole consumer of the IXFactory abstraction, you are decoupling something that doesn't require decoupling: The Composition Root intrinsically knows about every other part of the system any way.

            This seems to be the case with your IGeneticAlgorithmFactory abstraction. Its sole consumer seems to be your Composition Root. If this is true, this abstraction and its implementation can simply be removed and the code within its getInstance method can simply be moved into the MainProgram class (which functions as your Composition Root).

            It's hard for me to understand whether or not your IIndividual implementations require a factory (it has been at least 14 years ago since I implemented a genetic algorithm at the University), but they seem more like runtime data rather than 'real' dependencies. So a factory might make sense here, although do verify whether their creation and implementation must be hidden behind an abstraction. I could imagine the application to be sufficiently loosely coupled when the FastGeneticAlgorithm creates SmallIndividual instances directly. This, however, is just a wild guess.

            On top of that, best practice is to apply Constructor Injection. This prevents Temporal Coupling. Furthermore, refrain specifying the implementations dependencies in the defined abstractions, as your AbstractGeneticAlgorithm does. This makes the abstraction a Leaky Abstraction (which is a DIP violation). Instead, declare the dependencies by declaring them as constructor arguments on the implementation (FastGeneticAlgorithm in your case).

            But even with the existence of the IIndividualFactory, your code can be simplified by following best practices as follows:



            import GeneticAlgorithm ModuleNotFoundError: No module named 'libs.GeneticAlgorithm'
            Asked 2019-Jun-17 at 12:19

            I have been trying to run a code a found and I get this kind of error . I don't know how to deal with this because I am new to python and trying to understand the concept of TSP problem. Any help would be appreciated Code below



            Answered 2019-Feb-24 at 22:26

            If you "found" this code (most probably on the internet?) then the one who posted this had a libs folder in his machine, with a module in it, so you either find this GeneticAlgorhythm module, or you won't be able to run this code successfully.

            When you see, in python from import Foo, Python is going to look for the bar module into the baz folder, and import class Foo from it. So you need to have baz module on your PC, or else that error will appear



            ArrayList objects are overridden
            Asked 2017-May-18 at 15:03

            Trying to work on a genetic algorithm here and I can't figure out why the same Array returns different results a few lines later.

            This is the code:



            Answered 2017-May-17 at 17:25

            Trying to work on a genetic algorithm here and I can't figure out why the same Array returns different results a few lines later.

            Each Solution is passed in a list of Vessel objects. This list is used to create another list of vessels inside each Solution but it's important to note that the new list still contains the original Vessel objects.



            MPI_Isend and MPI_Irecv running into segmentation fault
            Asked 2017-Mar-28 at 07:17

            I am using MPI to parallellize my C++ interplanetary trajectory optimization program. A huge part of that is being able to distribute the load to multiple worker nodes, have them do some computations on the data distributed, and return the data back to master node. I use asynchronous communication routines MPI_Isend and MPI_Irecv in my program along with MPI_Wait appropriately I think. However I am running into abrupt program termination with EXIT CODE: 11, which I think stands for a segmentation fault. I have tried a thorough search on Stack Overflow on this topic and made sure to cover mistakes others were making in their code. My code however, still does not work. Here is the code:



            Answered 2017-Mar-27 at 11:34

            At least one critical MPI_Wait is commented out.


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install GeneticAlgorithm

            You can download it from GitHub.
            You can use GeneticAlgorithm like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the GeneticAlgorithm component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer For Gradle installation, please refer .


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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