src.environment.problem.basic_problem

Module Contents

Classes

Basic_Problem	Abstract super class for problems and applications.
Basic_Problem_Torch	Abstract super class for problems and applications.

API

class src.environment.problem.basic_problem.Basic_Problem

Abstract super class for problems and applications.

reset()

Introduction

Resets the environment state by initializing or clearing relevant attributes.The basic solution is to set T1 to 0.

Args:

None

Returns:

None

Raises:

None

eval(x)

Introduction

Evaluates the objective function for either a single individual or a population, adapting the input as needed. Also measures and accumulates the evaluation time.

Args:

• x (array-like or np.ndarray): Input vector(s) representing either a single individual (1D array) or a population (2D array).

Returns:

• float or np.ndarray: The evaluated result(s) from the objective function. Returns a single value for an individual or an array for a population.

Raises:

• None explicitly, but may raise exceptions from the underlying func or if input shapes are incompatible.

abstractmethod func(x)

class src.environment.problem.basic_problem.Basic_Problem_Torch

Bases: src.environment.problem.basic_problem.Basic_Problem

Abstract super class for problems and applications.

reset()

Introduction

Resets the environment state by initializing or clearing relevant attributes.

Args:

None

Returns:

None

eval(x)

Introduction

Evaluates the objective function for a given individual or population, handling input adaptation and timing the evaluation process.

Args:

• x (torch.Tensor or array-like): Input data representing either a single individual (1D) or a population (2D or higher). If not a torch.Tensor, it will be converted.

Returns:

• torch.Tensor: The evaluated result(s) from the objective function, matching the input shape.

Notes:

• Automatically adapts input to the correct shape and dtype (torch.float64).

• Measures and accumulates the evaluation time in milliseconds in self.T1.

• Temporarily sets the default torch device to match the input tensor’s device during evaluation.

abstractmethod func(x)

Introduction

Abstract method to be implemented by subclasses, defining the specific evaluation function for the problem.

Args:

• x: Input parameter to be processed by the function. The type and purpose should be defined in the subclass implementation.

Returns:

• Any: The result of processing x. The return type should be specified in the subclass.

Raises:

• NotImplementedError: Always raised to indicate that this method must be implemented by a subclass.