opytimizer.optimizers.evolutionary.bsa¶
Backtracking Search Optimization Algorithm.
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class
opytimizer.optimizers.evolutionary.bsa.
BSA
(params: Optional[Dict[str, Any]] = None)¶ A BSA class, inherited from Optimizer.
This is the designed class to define BSOA-related variables and methods.
References
P. Civicioglu. Backtracking search optimization algorithm for numerical optimization problems. Applied Mathematics and Computation (2013).
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__init__
(params: Optional[Dict[str, Any]] = None) → None¶ Initialization method.
Parameters: params – Contains key-value parameters to the meta-heuristics.
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F
¶ Experience from previous generation.
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mix_rate
¶ Number of non-crosses.
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old_agents
¶ List of historical agents.
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compile
(space: opytimizer.core.space.Space) → None¶ Compiles additional information that is used by this optimizer.
Parameters: space – A Space object containing meta-information.
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_permute
(agents: List[opytimizer.core.agent.Agent]) → None¶ Performs the permuting operator.
Parameters: agents – List of agents.
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_mutate
(agents: List[opytimizer.core.agent.Agent]) → List[opytimizer.core.agent.Agent]¶ Performs the mutation operator.
Parameters: agents – List of agents. Returns: A list holding the trial agents. Return type: (List[Agent])
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_crossover
(agents: List[opytimizer.core.agent.Agent], trial_agents: List[opytimizer.core.agent.Agent]) → None¶ Performs the crossover operator.
Parameters: - agents – List of agents.
- trial_agents – List of trial agents.
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update
(space: opytimizer.core.space.Space, function: opytimizer.core.function.Function) → None¶ Wraps Backtracking Search Optimization Algorithm over all agents and variables.
Parameters: - space – Space containing agents and update-related information.
- function – A Function object that will be used as the objective function.
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