GeneticAlgorithm | 遗传算法的JS实现

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:

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

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

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:

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 GeneticAlgorhythm.py 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 baz.bar 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

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.

At least one critical MPI_Wait is commented out.