CriticalPath analysis

CriticalPath analysis#

This notebook provides an example of a simulation that takes a number of sub_processes, grouped in a SequentialActivity, that is executed in a WhileActivity while a stop condition is not yet met.

For this example we work with the following sub_processes:

sailing empty
loading
sailing full
unloading

After the simulation is run a gantt chart with the critical path is visualised. Note that the simulation is run with an environment within OpenClSim (which is designed for the purpose of extracting the critical path) and not with simpy.Environment.

0. Import libraries#

import datetime, time
import simpy

import shapely.geometry
import pandas as pd

import openclsim.core as core
import openclsim.model as model
import openclsim.plot as plot
from openclsim.critical_path.dependencies_from_simpy_step import DependenciesFromSimpy, CriticalPathEnvironment

1. Initialise simpy environment#

# setup environment
my_env = CriticalPathEnvironment(initial_time=0)

2. Define object classes#

# create a Site object based on desired mixin classes
Site = type(
    "Site",
    (
        core.Identifiable,
        core.Log,
        core.Locatable,
        core.HasContainer,
        core.HasResource,
    ),
    {},
)

# create a TransportProcessingResource object based on desired mixin classes
TransportProcessingResource = type(
    "TransportProcessingResource",
    (
        core.ContainerDependentMovable,
        core.Processor,
        core.HasResource,
        core.LoadingFunction,
        core.UnloadingFunction,
        core.Identifiable,
        core.Log,
    ),
    {},
)

3. Create objects#

3.1. Create site object(s)#

# prepare input data for from_site
location_from_site = shapely.geometry.Point(4.18055556, 52.18664444)
data_from_site = {"env": my_env,
                  "name": "from_site",
                  "geometry": location_from_site,
                  "capacity": 100,
                  "level": 100
                 }
# instantiate from_site 
from_site = Site(**data_from_site)

# prepare input data for to_site
location_to_site = shapely.geometry.Point(4.25222222, 52.11428333)
data_to_site = {"env": my_env,
                "name": "to_site",
                "geometry": location_to_site,
                "capacity": 100,
                "level": 0
               }
# instantiate to_site 
to_site = Site(**data_to_site)

3.2. Create vessel object(s)#

# prepare input data for vessel_01
data_vessel01 = {"env": my_env,
                 "name": "vessel01",
                 "geometry": location_from_site, 
                 "loading_rate": 0.0004,
                 "unloading_rate": 0.0004,
                 "capacity": 4,
                 "compute_v": lambda x: 10
               }
# instantiate vessel_01 
vessel01 = TransportProcessingResource(**data_vessel01)

3.3 Create activity/activities#

# initialise registry
registry = {}

# create a list of the sub processes
sub_processes = [
    model.MoveActivity(
        env=my_env,
        name="sailing empty",
        registry=registry,
        mover=vessel01,
        destination=from_site,
    ),
    model.ShiftAmountActivity(
        env=my_env,
        name="loading",
        registry=registry,
        processor=vessel01,
        origin=from_site,
        destination=vessel01,
        amount=4,
        duration=1000,
    ),
    model.MoveActivity(
        env=my_env,
        name="sailing full",
        registry=registry,
        mover=vessel01,
        destination=to_site,
    ),
    model.ShiftAmountActivity(
        env=my_env,
        name="unloading",
        registry=registry,
        processor=vessel01,
        origin=vessel01,
        destination=to_site,
        amount=4,
        duration=1000,
    ),
    model.BasicActivity(
        env=my_env,
        name="basic activity",
        registry=registry,
        duration=0,
        additional_logs=[vessel01],
    ),
]

# create a 'sequential activity' that is made up of the 'sub_processes'
sequential_activity = model.SequentialActivity(
        env=my_env,
        name="sequential",
        registry=registry,
        sub_processes=sub_processes,
    )

# create a while activity that executes the 'sequential activity' while the stop condition is not triggered 
while_activity = model.WhileActivity(
    env=my_env,
    name="while",
    registry=registry,
    sub_processes=[sequential_activity],
    condition_event=[{"type": "container", "concept": to_site, "state": "full"}],
)

4. Register processes and run simpy#

# initate the simpy processes defined in the 'while activity' and run simpy
model.register_processes([while_activity])
my_env.run()

5. Inspect results#

5.1 Inspect logs#

plot.get_log_dataframe(vessel01, [while_activity])

	Activity	Timestamp	ActivityState	container level	geometry	type	ref
0	sailing empty	1970-01-01 00:00:00.000000	START	0.0	POINT (4.18055556 52.18664444)	NaN	NaN
1	sailing empty	1970-01-01 00:00:00.000000	STOP	0.0	POINT (4.18055556 52.18664444)	NaN	NaN
2	loading	1970-01-01 00:00:00.000000	START	0.0	POINT (4.18055556 52.18664444)	NaN	NaN
3	loading	1970-01-01 00:16:40.000000	STOP	4.0	POINT (4.18055556 52.18664444)	NaN	NaN
4	sailing full	1970-01-01 00:16:40.000000	START	4.0	POINT (4.18055556 52.18664444)	NaN	NaN
...	...	...	...	...	...	...	...
245	sailing full	1970-01-02 02:26:38.404972	STOP	4.0	POINT (4.25222222 52.11428333)	NaN	NaN
246	unloading	1970-01-02 02:26:38.404972	START	4.0	POINT (4.25222222 52.11428333)	NaN	NaN
247	unloading	1970-01-02 02:43:18.404972	STOP	0.0	POINT (4.25222222 52.11428333)	NaN	NaN
248	basic activity	1970-01-02 02:43:18.404972	START	0.0	POINT (4.25222222 52.11428333)	additional log	96f1d46a-a682-44eb-bbbd-5c51c62ea42f
249	basic activity	1970-01-02 02:43:18.404972	STOP	0.0	POINT (4.25222222 52.11428333)	additional log	96f1d46a-a682-44eb-bbbd-5c51c62ea42f

250 rows × 7 columns

5.2 Visualise gantt charts#

plot.get_gantt_chart([while_activity])

plot.get_gantt_chart([vessel01, from_site, to_site],id_map=[while_activity])

5.3 Visualise container volume developments#

fig = plot.get_step_chart([vessel01, from_site, to_site])

../_images/2bec3873e8128b0d1390488968d4d5cf054ee4b7115c76c6ace0e99daf808b50.png

5.4 Visualise critical path#

Determine critical path with method ‘from simpy’. One can investigate the activities on the critical path through inspection of the dataframe with recorded activities or through a gannt chart.

my_cp_dependencies_from_simpy = DependenciesFromSimpy(env=my_env, 
                                                      object_list=[vessel01, from_site, to_site],
                                                      activity_list=[while_activity])
critical_df = my_cp_dependencies_from_simpy.get_critical_path_df()
print("An overview of recorded activities, with an indication if activity is on critical path (column 'is_critical')")
critical_df

An overview of recorded activities, with an indication if activity is on critical path (column 'is_critical')

	ActivityID	Activity	SimulationObject	start_time	end_time	duration	state	cp_activity_id	is_critical
1	f22afd72-13aa-4b38-8d1d-28c93acdc36f	loading	from_site	1970-01-01 00:00:00.000000	1970-01-01 00:16:40.000000	0 days 00:16:40	ACTIVE	79239fec-36f8-4a3b-9069-67d099c1cabb	True
2	f22afd72-13aa-4b38-8d1d-28c93acdc36f	loading	vessel01	1970-01-01 00:00:00.000000	1970-01-01 00:16:40.000000	0 days 00:16:40	ACTIVE	79239fec-36f8-4a3b-9069-67d099c1cabb	True
4	49eafd9c-23fe-43c3-8bbb-40923f84d8cd	sailing empty	vessel01	1970-01-01 00:00:00.000000	1970-01-01 00:00:00.000000	0 days 00:00:00	ACTIVE	0a37f983-626f-4cd1-9f96-1dbeb601d7eb	False
11	16f6278f-7bb3-4299-b4b2-3742326cb0ed	sailing full	vessel01	1970-01-01 00:16:40.000000	1970-01-01 00:32:22.824591	0 days 00:15:42.824591	ACTIVE	056fc0f7-233b-4bf8-89ad-95b1944d09e6	True
15	8ad97efb-f073-4368-a54b-c4db7144e147	unloading	to_site	1970-01-01 00:32:22.824591	1970-01-01 00:49:02.824591	0 days 00:16:40	ACTIVE	ea4ee3ce-26ef-4190-bac6-4d1603fcbd27	True
...	...	...	...	...	...	...	...	...	...
464	f22afd72-13aa-4b38-8d1d-28c93acdc36f	loading	vessel01	1970-01-02 01:54:15.580381	1970-01-02 02:10:55.580381	0 days 00:16:40	ACTIVE	a13272f8-88ff-46ea-b60f-9cad1781ab71	True
467	16f6278f-7bb3-4299-b4b2-3742326cb0ed	sailing full	vessel01	1970-01-02 02:10:55.580381	1970-01-02 02:26:38.404972	0 days 00:15:42.824591	ACTIVE	e8bb1673-2972-4284-a13b-97191c4baa24	True
471	8ad97efb-f073-4368-a54b-c4db7144e147	unloading	to_site	1970-01-02 02:26:38.404972	1970-01-02 02:43:18.404972	0 days 00:16:40	ACTIVE	e077283c-f164-42aa-98f1-a3d925954772	True
472	8ad97efb-f073-4368-a54b-c4db7144e147	unloading	vessel01	1970-01-02 02:26:38.404972	1970-01-02 02:43:18.404972	0 days 00:16:40	ACTIVE	e077283c-f164-42aa-98f1-a3d925954772	True
474	96f1d46a-a682-44eb-bbbd-5c51c62ea42f	basic activity	vessel01	1970-01-02 02:43:18.404972	1970-01-02 02:43:18.404972	0 days 00:00:00	ACTIVE	52936c37-1578-4642-9426-8b2d88476dc8	False

175 rows × 9 columns

my_cp_dependencies_from_simpy.make_plotly_gantt_chart()