opytimizer.optimizers.swarm.js¶

Jellyfish Search-based algorithms.

class opytimizer.optimizers.swarm.js.JS(params: Optional[Dict[str, Any]] = None)¶

A JS class, inherited from Optimizer.

This is the designed class to define JS-related variables and methods.

References

J.-S. Chou and D.-N. Truong. A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean. Applied Mathematics and Computation (2020).

__init__(params: Optional[Dict[str, Any]] = None) → None¶

Initialization method.

Parameters:	params – Contains key-value parameters to the meta-heuristics.

_initialize_chaotic_map(agents: List[opytimizer.core.agent.Agent]) → None¶

Initializes a set of agents using a logistic chaotic map.

Parameters:	agents – List of agents.

compile(space: opytimizer.core.space.Space) → None¶

Compiles additional information that is used by this optimizer.

Parameters:	space – A Space object containing meta-information.

_ocean_current(agents: List[opytimizer.core.agent.Agent], best_agent: opytimizer.core.agent.Agent) → numpy.ndarray¶

Calculates the ocean current (eq. 9).

Parameters:	agents – List of agents. best_agent – Best agent.
Returns:	A trend value for the ocean current.
Return type:	(np.ndarray)

_motion_a(lb: numpy.ndarray, ub: numpy.ndarray) → numpy.ndarray¶

Calculates type A motion (eq. 12).

Parameters:	lb – Array of lower bounds. ub – Array of upper bounds.
Returns:	A type A motion array.
Return type:	(np.ndarray)

_motion_b(agent_i: opytimizer.core.agent.Agent, agent_j: opytimizer.core.agent.Agent) → numpy.ndarray¶

Calculates type B motion (eq. 15).

Parameters:	agent_i – Current agent to be updated. agent_j – Selected agent.
Returns:	A type B motion array.
Return type:	(np.ndarray)

update(space: opytimizer.core.space.Space, iteration: int, n_iterations: int) → None¶

Wraps Jellyfish Search over all agents and variables.

Parameters:	space – Space containing agents and update-related information. iteration – Current iteration. n_iterations – Maximum number of iterations.

class opytimizer.optimizers.swarm.js.NBJS(params: Optional[Dict[str, Any]] = None)¶

An NBJS class, inherited from JS.

This is the designed class to define NBJS-related variables and methods.

References

Publication pending.

__init__(params: Optional[Dict[str, Any]] = None) → None¶

Initialization method.

Parameters:	params – Contains key-value parameters to the meta-heuristics.

_motion_a(lb: numpy.ndarray, ub: numpy.ndarray) → numpy.ndarray¶

Calculates type A motion.

Parameters:	lb – Array of lower bounds. ub – Array of upper bounds.
Returns:	A type A motion array.
Return type:	(np.ndarray)