Implement an OOP/OOD Monte Carlo discrete event simulation with the following features for Implement an OOP/OOD Monte Carlo discrete event simulation with the following features for

the crude oil pipeline network operation: the crude oil pipeline network operation:

1) Create a population of 16 stations for petrol extraction, with 16 tanks, and 16 pumps; the

1) Create a population of 16 stations for petrol extraction, with 16 tanks, and 16 pumps; the

distances between each oil extraction is 20 miles; they are evenly distributed in a V shape

distances between each oil extraction is 20 miles; they are evenly distributed in a V shape

layout; (1 point) layout; (1 point)

2) Make the data representation of the problem associating as required to make the model

2) Make the data representation of the problem associating as required to make the model

implementation; (1 point) implementation; (1 point)

3) Define a rule or strategy to optimize the pipeline optimization; try stabilized the system, 3) Define a rule or strategy to optimize the pipeline optimization; try stabilized the system,

with the volume of storage tank around 50%; simulate a dynamic 48 hours scenario; (1 point) with the volume of storage tank around 50%; simulate a dynamic 48 hours scenario; (1 point)

4) Initialize the levels of the tanks with average 40% of their storage capacity and variance

4) Initialize the levels of the tanks with average 40% of their storage capacity and variance

standard deviation of 10; assume that each tank having a total capacity for storage of 100

standard deviation of 10; assume that each tank having a total capacity for storage of 100

gallons; (1 point) gallons; (1 point)

5) Assume that the input per tank is 10 gallons per hour in average with standard deviation of

5) Assume that the input per tank is 10 gallons per hour in average with standard deviation of

3; (1 point) 3; (1 point)

6) The pipeline total capacity is to dispatch 200 gallons per hour with all pumps turned on; 6) The pipeline total capacity is to dispatch 200 gallons per hour with all pumps turned on;

each pump can on average dispatch 12 gallons per hour with a random standard deviation of each pump can on average dispatch 12 gallons per hour with a random standard deviation of

2 gallons; (1 point) 2 gallons; (1 point)

7) Define what is the best time scale for you time step simulation using quantitative data to

7) Define what is the best time scale for you time step simulation using quantitative data to

compare the pros and cons; (1 point) compare the pros and cons; (1 point)

8) Using python, create a histogram show the tank levels along the time step simulation,

8) Using python, create a histogram show the tank levels along the time step simulation,

highest and lowest tank levels; (1 point) highest and lowest tank levels; (1 point)

9) Create a table with the state of each pump and the level of each tank along the simulation; 9) Create a table with the state of each pump and the level of each tank along the simulation;

(1 point)

(1 point)

10) Create a solution that will reach following goals: (a) try to keep the tank levels closest to

10) Create a solution that will reach following goals: (a) try to keep the tank levels closest to

50%; (b) maximize the lifespan of the pipeline; (c) minimize the electricity consumption; (d)

50%; (b) maximize the lifespan of the pipeline; (c) minimize the electricity consumption; (d)

keep the delivery flow as close as possible to a constant flow at 160 gallons per hour; (1 keep the delivery flow as close as possible to a constant flow at 160 gallons per hour; (1

point)

point)