diff --git a/docs/api/_pyswarms.utils.rst b/docs/api/_pyswarms.utils.rst
index a7e81225..bf8dd659 100644
--- a/docs/api/_pyswarms.utils.rst
+++ b/docs/api/_pyswarms.utils.rst
@@ -10,4 +10,3 @@ functionalities.
    pyswarms.utils.functions
    pyswarms.utils.search
    pyswarms.utils.plotters
-   pyswarms.utils.environments
diff --git a/docs/api/pyswarms.utils.environments.rst b/docs/api/pyswarms.utils.environments.rst
deleted file mode 100644
index 907e20b4..00000000
--- a/docs/api/pyswarms.utils.environments.rst
+++ /dev/null
@@ -1,17 +0,0 @@
-pyswarms.utils.environments package
-====================================
-
-.. automodule:: pyswarms.utils.environments
-
-.. deprecated:: 0.2.1
-   This module will be deprecated in the next release. Please use
-   :mod:`pyswarms.utils.plotters` instead.
-
-pyswarms.utils.environments.plot_environment module
-----------------------------------------------------
-
-.. automodule:: pyswarms.utils.environments.plot_environment
-   :members:
-   :undoc-members:
-   :show-inheritance:
-   :special-members: __init__
\ No newline at end of file
diff --git a/pyswarms/utils/environments/__init__.py b/pyswarms/utils/environments/__init__.py
deleted file mode 100644
index 2207de52..00000000
--- a/pyswarms/utils/environments/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-"""
-The mod:`pyswarms.utils.environments` module implements various
-optimization environments to analyze optimizer performance or search
-better parameters
-"""
-
-from .plot_environment import PlotEnvironment
-
-__all__ = ["PlotEnvironment"]
diff --git a/pyswarms/utils/environments/plot_environment.py b/pyswarms/utils/environments/plot_environment.py
deleted file mode 100644
index 6e9321d3..00000000
--- a/pyswarms/utils/environments/plot_environment.py
+++ /dev/null
@@ -1,472 +0,0 @@
-# -*- coding: utf-8 -*-
-
-r"""
-Plot environment for Optimizer Analysis
-
-.. deprecated:: 0.2.1
-   This module will be deprecated in the next release. Please use
-   :mod:`pyswarms.utils.plotters` instead.
-
-The class PlotEnvironment is built on top of :code:`matplotlib` in order
-to render quick and easy plots for your optimizer. It can plot the best
-cost for each iteration, and show animations of the particles in 2-D and
-3-D space. Furthermore, because it has :code:`matplotlib` running under
-the hood, the plots are easily customizable.
-
-For example, if we want to plot the cost using PlotEnvironment, simply
-pass the optimizer object when initializing the class, and the
-PlotEnvironment will do a fresh run of your optimizer. After that,
-various plotting methods can now be done:
-
-.. code-block:: python
-
-    import pyswarms as ps
-    from pyswarms.utils.functions.single_obj import sphere_func
-    from pyswarms.utils.environments import PlotEnvironment
-
-    # Set up optimizer
-    options = {'c1':0.5, 'c2':0.3, 'w':0.9}
-    optimizer = ps.single.GlobalBestPSO(n_particles=10, dimensions=2,
-                                        options=options)
-
-    # Pass optimizer  inside the environment. You also need to pass some
-    # of the required arguments on how your optimizer will be evaluated.
-    plt_env = PlotEnvironment(optimizer, sphere_func, 1000)
-
-    # To plot the cost
-    plt_env.plot_cost()
-    plt.show()
-
-In case you want to plot the particle movement, it is important that either
-one of the :code:`matplotlib` animation :code:`Writers` is installed. These
-doesn't come out of the box for :code:`pyswarms`, and must be installed
-separately. For example, in a Linux or Windows distribution, you can install
-:code:`ffmpeg` as
-
-    >>> conda install -c conda-forge ffmpeg
-
-Now, if you want to plot your particles in a 2-D environment, simply call
-the following function:
-
-    >>> plt_env.plot_particles2d()
-
-You can also supply various arguments in this method: the indices of the
-specific dimensions to be used, the limits of the axes, and the interval/
-speed of animation.
-"""
-
-# Import from __future__
-from __future__ import with_statement
-from __future__ import absolute_import
-from __future__ import print_function
-
-# Import modules
-import logging
-import warnings
-import numpy as np
-import matplotlib.pyplot as plt
-from past.builtins import xrange
-from matplotlib import animation
-from collections import namedtuple
-from mpl_toolkits.mplot3d import Axes3D
-
-warnings.simplefilter("default")
-warnings.warn(
-    "The pyswarms.environments module is deprecated and will be removed in v.0.2.5. For visualization, please use pyswarms.plotters",
-    DeprecationWarning,
-    stacklevel=2,
-)
-
-
-class PlotEnvironment(object):
-    def assertions(self):
-        """Check inputs and throw assertions"""
-        # Check if the objective_func is a callable
-        if not callable(self.objective_func):
-            raise TypeError("Must pass a callable")
-
-        # Check if getters exist in the optimizer
-        if not (
-            hasattr(self.optimizer, "get_cost_history")
-            & hasattr(self.optimizer, "get_pos_history")
-            & hasattr(self.optimizer, "get_velocity_history")
-        ):
-            raise AttributeError(
-                "Missing getters in optimizer, check " "pyswarms.base module"
-            )
-
-        # Check if important methods exist in the optimizer
-        if not (
-            hasattr(self.optimizer, "optimize")
-            & hasattr(self.optimizer, "reset")
-        ):
-            raise AttributeError(
-                "Missing methods in optimizer, check " "pyswarms.base module"
-            )
-
-    def __init__(self, optimizer, objective_func, iters):
-        """Run the optimizer against an objective function for a number
-        of iterations
-
-        Upon initialization, the :code:`optimize` method of the optimizer
-        will be called, passing the arguments :code:`objective_func` and
-        :code:`iters`. The results of the optimization scheme is then
-        stored as attributes of this class.
-
-        Parameters
-        ----------
-        optimizer : object instance
-            An instance of an optimizer class that was derived from any
-            of the :mod:`pyswarms.base` classes.
-        objective_func : method
-            An objective function to be optimized using the :code:`optimizer`.
-            This argument is passed to the :code:`optimize` method of the
-            :code:`optimizer`.
-        iters : int
-            The number of iterations to run the optimizer. This argument
-            is passed to the :code:`optimize` method of the :code:`optimizer`.
-        """
-        self.logger = logging.getLogger(__name__)
-        # Store the arguments
-        self.optimizer = optimizer
-        self.objective_func = objective_func
-        self.iters = iters
-        # Check assertions
-        self.assertions()
-        # Run the optimizer
-        self.optimizer.reset()
-        self.status = self.optimizer.optimize(objective_func, iters, 1, 0)
-        # Initialize tuples for particle plotting
-        self.Index = namedtuple("Index", ["x", "y", "z"])
-        self.Limit = namedtuple("Limit", ["x", "y", "z"])
-        self.Label = namedtuple("Label", ["x", "y", "z"])
-
-    def plot_cost(
-        self,
-        title="Cost History",
-        ax=None,
-        figsize=None,
-        title_fontsize="large",
-        text_fontsize="medium",
-        **kwargs
-    ):
-        """Create a simple line plot with the cost in the y-axis and
-        the iteration at the x-axis
-
-        Parameters
-        ----------
-        title : str (default is :code:`'Cost History'`)
-            The title of the plotted graph.
-        ax : :class:`matplotlib.axes.Axes` (default is :code:`None`)
-            The axes where the plot is to be drawn. If :code:`None` is
-            passed, then the plot will be drawn to a new set of axes.
-        figsize : tuple (default is None)
-            Sets the size of the plot figure.
-        title_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of the title. Available values are
-            ['small', 'medium', 'large'] or integer values.
-        text_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of various texts around the plot.
-            Available values are ['small', 'medium', 'large'] or integer
-            values.
-        **kwargs : dict
-            Keyword arguments that are passed as a keyword argument to
-            :class:`matplotlib.axes.Axes`
-
-        Returns
-        -------
-        :class:`matplotlib.axes._subplots.AxesSubplot`
-            The axes on which the plot was drawn.
-        """
-        # Get cost history from the optimizer method
-        cost_history = self.optimizer.get_cost_history
-        mean_pbest_history = self.optimizer.get_mean_pbest_history
-        mean_neighbor_history = self.optimizer.get_mean_neighbor_history
-
-        # If ax is default, then create new plot
-        if ax is None:
-            fig, ax = plt.subplots(1, 1, figsize=figsize)
-
-        # Plot with self.iters as x-axis and cost_history as
-        # y-axis.
-        ax.plot(
-            np.arange(self.iters), cost_history, "k", lw=2, label="Best cost"
-        )
-        ax.plot(
-            np.arange(self.iters),
-            mean_pbest_history,
-            "k--",
-            lw=2,
-            label="Avg. personal best cost",
-        )
-        ax.plot(
-            np.arange(self.iters),
-            mean_neighbor_history,
-            "k:",
-            lw=2,
-            label="Avg. neighborhood cost",
-        )
-
-        # Customize plot depending on parameters
-        ax.set_title(title, fontsize=title_fontsize)
-        ax.legend(fontsize=text_fontsize)
-        ax.set_xlabel("Iterations", fontsize=text_fontsize)
-        ax.set_ylabel("Cost", fontsize=text_fontsize)
-        ax.tick_params(labelsize=text_fontsize)
-
-        return ax
-
-    def plot_particles2D(
-        self,
-        index=(0, 1),
-        limits=((-1, 1), (-1, 1)),
-        labels=("x-axis", "y-axis"),
-        interval=80,
-        title="Particle Movement in 2D space",
-        ax=None,
-        figsize=None,
-        title_fontsize="large",
-        text_fontsize="medium",
-    ):
-        """Create an animation of particle movement in 2D-space
-
-        Parameters
-        ----------
-        index : n-tuple (default is :code:`(0,1)`)
-            The index in which a specific dimension will be plotted. For
-            example, :code:`(idx_1, idx_2)` for two dimensions.
-        limits : n-tuple of 2-tuples (default is :code:`((-1,1),(-1,1))`)
-            The limits of the x-y axes for 2D. For example,
-            :code:`((xmin, xmax),(ymin, ymax))`
-        labels : 2-tuple (default is :code:`('x-axis', 'y-axis')`
-            Sets the x and y labels of the 2D plot. For example,
-            :code:`('label_x_axis', 'label_y_axis')`
-        interval : int (default is 80)
-            The speed of update, in milliseconds
-        title : str (default is :code:`'Particle Movement in 2D space'`)
-            The title of the plotted graph.
-        ax : :class:`matplotlib.axes.Axes` (default is :code:`None`)
-            The axes where the plot is to be drawn. If :code:`None` is
-            passed, then the plot will be drawn to a new set of axes.
-        figsize : tuple (default is None)
-            Sets the size of the plot figure.
-        title_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of the title. Available values are
-            ['small', 'medium', 'large'] or integer values.
-        text_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of various texts around the plot.
-            Available values are ['small', 'medium', 'large'] or integer
-            values.
-        **kwargs : dict
-            Keyword arguments that are passed as a keyword argument to
-            :class:`matplotlib.axes.Axes`
-
-        Returns
-        -------
-        :class:`matplotlib.animation.FuncAnimation`
-            The drawn animation that can be saved to mp4 or other
-            third-party tools
-        """
-        # Check inconsistencies with input
-        if not (len(index) == len(limits) == 2):
-            raise ValueError("The index and limits should be of length 2")
-
-        # Set-up tuples for plotting environment
-        idx = self.Index(x=index[0], y=index[1], z=None)
-        lmt = self.Limit(x=limits[0], y=limits[1], z=None)
-        lbl = self.Label(x=labels[0], y=labels[1], z=None)
-
-        # If ax is default, then create new plot. Set-up the figure, the
-        # acis, and the plot element that we want to animate
-        if ax is None:
-            fig, ax = plt.subplots(1, 1, figsize=figsize)
-
-        # Set plot title
-        ax.set_title(title, fontsize=title_fontsize)
-
-        # Set plot labels
-        ax.set_xlabel(lbl.x, fontsize=text_fontsize)
-        ax.set_ylabel(lbl.y, fontsize=text_fontsize)
-
-        # Set plot limits
-        ax.set_xlim(lmt.x)
-        ax.set_ylim(lmt.y)
-
-        # Plot data
-        plot = ax.scatter(x=[], y=[], c="red")
-        data = self.optimizer.get_pos_history
-
-        # Get the number of iterations
-        n_iters = self.optimizer.get_pos_history.shape[0]
-
-        # Perform animation
-        anim = animation.FuncAnimation(
-            fig,
-            func=self._animate2D,
-            frames=xrange(n_iters),
-            fargs=(data, plot, idx),
-            interval=interval,
-            blit=True,
-        )
-        return anim
-
-    def plot_particles3D(
-        self,
-        index=(0, 1, 2),
-        limits=((-1, 1), (-1, 1), (-1, 1)),
-        labels=("x-axis", "y-axis", "z-axis"),
-        interval=80,
-        title="Particle Movement in 3D space",
-        ax=None,
-        figsize=None,
-        title_fontsize="large",
-        text_fontsize="medium",
-    ):
-        """Create an animation of particle movement in 3D-space
-
-        Parameters
-        ----------
-        index : n-tuple (default is :code:`(0,1,2)`)
-            The index in which a specific dimension will be plotted. For
-            example, :code:`(idx_1, idx_2, idx_3)` for three dimensions.
-        limits : n-tuple of 2-tuples (default is
-                 :code:`((-1,1),(-1,1),(-1,1))`)
-            The limits of the x-y axes for 3D. For example,
-            :code:`((xmin, xmax),(ymin, ymax))`
-        labels : 2-tuple (default is :code:`('x-axis', 'y-axis', 'z-axis')`
-            Sets the x and y labels of the 2D plot. For example,
-            :code:`('label_x_axis', 'label_y_axis', 'label_z_axis')`
-        interval : int (default is 80)
-            The speed of update, in milliseconds
-        title : str (default is :code:`'Particle Movement in 3D space'`)
-            The title of the plotted graph.
-        ax : :class:`matplotlib.axes.Axes` (default is :code:`None`)
-            The axes where the plot is to be drawn. If :code:`None` is
-            passed, then the plot will be drawn to a new set of axes.
-        figsize : tuple (default is None)
-            Sets the size of the plot figure.
-        title_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of the title. Available values are
-            ['small', 'medium', 'large'] or integer values.
-        text_fontsize : str or int (default is :code:`large`)
-            This is a :class:`matplotlib.axes.Axes` argument that
-            specifies the size of various texts around the plot.
-            Available values are ['small', 'medium', 'large'] or integer
-            values.
-        **kwargs : dict
-            Keyword arguments that are passed as a keyword argument to
-            :class:`matplotlib.axes.Axes`
-
-        Returns
-        -------
-        :class:`matplotlib.animation.FuncAnimation`
-            The drawn animation that can be saved to mp4 or other
-            third-party tools
-        """
-        # Check inconsistencies with input
-        if not (len(index) == len(limits) == 3):
-            raise ValueError("The index and limits should be of length 3")
-
-        # Set-up tuples for plotting environment
-        idx = self.Index(x=index[0], y=index[1], z=index[2])
-        lmt = self.Limit(x=limits[0], y=limits[1], z=limits[2])
-        lbl = self.Label(x=labels[0], y=labels[1], z=labels[2])
-
-        # If ax is default, then create new plot. Set-up the figure, the
-        # acis, and the plot element that we want to animate
-        if ax is None:
-            fig, ax = plt.subplots(1, 1, figsize=figsize)
-            ax = Axes3D(fig)
-
-        # Set plot title
-        ax.set_title(title, fontsize=title_fontsize)
-
-        # Set plot axes labels
-        ax.set_xlabel(lbl.x, fontsize=text_fontsize)
-        ax.set_ylabel(lbl.y, fontsize=text_fontsize)
-        ax.set_zlabel(lbl.z, fontsize=text_fontsize)
-
-        # Set plot limits
-        ax.set_xlim(lmt.x)
-        ax.set_ylim(lmt.y)
-        ax.set_zlim(lmt.z)
-
-        # Plot data
-        plot = ax.scatter(xs=[], ys=[], zs=[], c="red")
-        data = self.optimizer.get_pos_history
-
-        # Get the number of iterations
-        n_iters = self.optimizer.get_pos_history.shape[0]
-
-        # Perform animation
-        anim = animation.FuncAnimation(
-            fig,
-            func=self._animate3D,
-            frames=xrange(n_iters),
-            fargs=(data, plot, idx),
-            interval=interval,
-        )
-        return anim
-
-    def _animate2D(self, i, data, plot, idx):
-        """Helper animation function that is called sequentially
-        :class:`matplotlib.animation.FuncAnimation`
-
-        Parameters
-        ----------
-        i : int
-            Required argument for :code:`matplotlib.animation.FuncAnimation`,
-            basis for indexing the current position of the swarm.
-        data : numpy.ndarray
-            The position matrix where the particles' position
-            will be taken from.
-        plot : matplotlib.Axes
-            The plot environment where the update operations will be drawn
-        idx : namedtuple
-            The chosen indices for plotting the dimensions
-
-        Returns
-        -------
-        :class:`matplotlib.artist.Artist`
-            iterable of artists
-        """
-        current_pos = data[i]
-        xy = current_pos[:, (idx.x, idx.y)]
-        plot.set_offsets(xy)
-        return (plot,)
-
-    def _animate3D(self, i, data, plot, idx):
-        """Helper animation function that is called sequentially
-        :class:`matplotlib.animation.FuncAnimation`
-
-        Parameters
-        ----------
-        i : int
-            Required argument for :code:`matplotlib.animation.FuncAnimation`,
-            basis for indexing the current position of the swarm.
-        data : numpy.ndarray
-            The position matrix where the particles' position
-            will be taken from.
-        plot : matplotlib.Axes
-            The plot environment where the update operations will be drawn
-        idx : namedtuple
-            The chosen indices for plotting the dimensions
-
-        Returns
-        -------
-        :class:`matplotlib.artist.Artist`
-            iterable of artists
-        """
-        current_pos = data[i]
-        x, y, z = (
-            current_pos[:, idx.x],
-            current_pos[:, idx.y],
-            current_pos[:, idx.z],
-        )
-        plot._offsets3d = (x, y, z)
-        return (plot,)
diff --git a/tests/utils/environments/__init__.py b/tests/utils/environments/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/utils/environments/conftest.py b/tests/utils/environments/conftest.py
deleted file mode 100644
index 1f548e9b..00000000
--- a/tests/utils/environments/conftest.py
+++ /dev/null
@@ -1,45 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-"""Fixtures for tests"""
-
-# Import modules
-import os
-import pytest
-from mock import Mock
-import matplotlib as mpl
-
-if os.environ.get("DISPLAY", "") == "":
-    mpl.use("Agg")
-
-# Import from package
-from pyswarms.single import GlobalBestPSO
-from pyswarms.utils.environments import PlotEnvironment
-from pyswarms.utils.functions.single_obj import sphere_func
-
-
-@pytest.fixture
-def mock_pso():
-    """Returns a function that mocks a PSO class with missing attributes"""
-
-    def _mock_pso(index):
-        class_methods = [
-            "cost_history",
-            "pos_history",
-            "velocity_history",
-            "optimize",
-            "reset",
-        ]
-        get_specs = lambda idx: [
-            x for i, x in enumerate(class_methods) if i != idx
-        ]
-        return Mock(spec=get_specs(index))
-
-    return _mock_pso
-
-
-@pytest.fixture
-def plot_environment():
-    """Returns a PlotEnvironment instance"""
-    optimizer = GlobalBestPSO(10, 3, options={"c1": 0.5, "c2": 0.3, "w": 0.9})
-    return PlotEnvironment(optimizer, sphere_func, 1000)
diff --git a/tests/utils/environments/test_plot_environment.py b/tests/utils/environments/test_plot_environment.py
deleted file mode 100644
index 600a5039..00000000
--- a/tests/utils/environments/test_plot_environment.py
+++ /dev/null
@@ -1,52 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-# Import modules
-import os
-import pytest
-import matplotlib as mpl
-
-if os.environ.get("DISPLAY", "") == "":
-    mpl.use("Agg")
-
-from matplotlib.axes._subplots import SubplotBase
-from matplotlib.animation import FuncAnimation
-
-# Import from package
-from pyswarms.utils.environments import PlotEnvironment
-from pyswarms.utils.functions.single_obj import sphere_func
-
-class_methods = [
-    "cost_history",
-    "pos_history",
-    "velocity_history",
-    "optimize",
-    "reset",
-]
-
-
-@pytest.mark.parametrize("attributes", [i for i in enumerate(class_methods)])
-def test_getters_pso(mock_pso, attributes):
-    """Tests an instance of the PSO class and should raise an exception when the class has missing attributes"""
-    idx, _ = attributes
-    with pytest.raises(AttributeError):
-        m = mock_pso(idx)
-        PlotEnvironment(m, sphere_func, 100)
-
-
-@pytest.mark.xfail
-def test_plot_cost_return_type(plot_environment):
-    """Tests if plot_cost() returns a SubplotBase instance"""
-    assert isinstance(plot_environment.plot_cost(), SubplotBase)
-
-
-@pytest.mark.xfail
-def test_plot2D_return_type(plot_environment):
-    """Test if plot_particles2D() returns a FuncAnimation instance"""
-    assert isinstance(plot_environment.plot_particles2D(), FuncAnimation)
-
-
-@pytest.mark.xfail
-def test_plot3D_return_type(plot_environment):
-    """Test if plot_particles3D() returns a FuncAnimation instance"""
-    assert isinstance(plot_environment.plot_particles3D(), FuncAnimation)