Write a program in python Using swarm basic optimization with arguments to find a minimum of Rosenbrook function, To find the minimum of the test function y = x – 2sin(x).set up the bound for the value [-5.12, 5.12].Use Swarm to find the value of X which minimizes the test function.Use the default hyperparameters.# hyperparametersoptions = {'c1': 0.5, 'c2': 0.3, 'w':0.9} Using ArgumentsArguments can either be passed in using a tuple or a dictionary, using the kwargs={} paradigm. Firstlets optimize the Rosenbrock function using keyword arguments. Note in the definition of theRosenbrock function above, there were two arguments that need to be passed other than thedesign variables, and one optional keyword argument, a, b, and c, respectively[7]: from pyswarms.single.global_best import GlobalBest PSO#instatiate the optimizerx_max = 10 np.ones (2)x_min = -1 * x_max*bounds = (x_min, x_max)options {'c1': 0.5, 'c2': 0.3, 'w': 0.9}optimizer = GlobalBest PSO(n_particles=10, dimensions=2, options=options, bounds-bounds)# now run the optimization, pass a=1 and b=100 as a tuple assigned to argscost, pos = optimizer.optimize(rosenbrock_with_args, 1000, a=1, b=100, c=0) Basic Optimization with ArgumentsHere, we will run a basic optimization using an objective function that needs parameterization. Wewill use the single. GBestPSO and a version of the rosenbrock function to demonstrate[6]: # import modulesimport numpy as np# create a parameterized version of the classic Rosenbrock unconstrained optimzation functiondef rosenbrock_with_args(x, a, b, c=0):f = (a - x[:, 0]) ** 2 + b * (x[:, 1] x[:, 0] ** 2) ** 2 + creturn f

1. Import numpy and pyswarms libraries2. Define the Rosenbrock function rosenbrock(x)Calculate the…

Answered: Write a program in python Using swarm…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

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Write a program in python Using swarm basic optimization with arguments to find a minimum of Rosenbrook function, To find the minimum of the test function y = x – 2sin(x).

set up the bound for the value [-5.12, 5.12].

Use Swarm to find the value of X which minimizes the test function.

Use the default hyperparameters.

# hyperparameters

options = {'c1': 0.5, 'c2': 0.3, 'w':0.9}

Using Arguments
Arguments can either be passed in using a tuple or a dictionary, using the kwargs={} paradigm. First
lets optimize the Rosenbrock function using keyword arguments. Note in the definition of the
Rosenbrock function above, there were two arguments that need to be passed other than the
design variables, and one optional keyword argument, a, b, and c, respectively
[7]: from pyswarms.single.global_best import GlobalBest PSO
#instatiate the optimizer
x_max = 10 np.ones (2)
x_min = -1 * x_max
*
bounds = (x_min, x_max)
options {'c1': 0.5, 'c2': 0.3, 'w': 0.9}
optimizer = GlobalBest PSO(n_particles=10, dimensions=2, options=options, bounds-bounds)
# now run the optimization, pass a=1 and b=100 as a tuple assigned to args
cost, pos = optimizer.optimize(rosenbrock_with_args, 1000, a=1, b=100, c=0)

Basic Optimization with Arguments
Here, we will run a basic optimization using an objective function that needs parameterization. We
will use the single. GBestPSO and a version of the rosenbrock function to demonstrate
[6]: # import modules
import numpy as np
# create a parameterized version of the classic Rosenbrock unconstrained optimzation function
def rosenbrock_with_args(x, a, b, c=0):
f = (a - x[:, 0]) ** 2 + b * (x[:, 1] x[:, 0] ** 2) ** 2 + c
return f

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What if the swarm was 2-dimentional and the max bound was 10* np.ones(2) and minimum bound = -1 *max.
How can I write a helper function that, given a vector/array A, returns a vector/array B in which
every element’s value is sine of the corresponding element’s value in A. For instance,
given array A=(e1 e2, e3), the helper function will return an array B=(sine(e1), sine(e2),
sine(e3)).

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