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D epartm ent ofEM IS SM U Schoolof Engineering Leadership in Engineering Systems Engineering for the Transportation Critical Infrastructure The Development of a Methodology and Mathematical Model for Assessing the Impacts of K Links Disconnects have on Defined Links of the Network

Terms and Definitions

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Page 1: Terms and Definitions

Department of EMISSMU School of Engineering

Leadership in Engineering

Systems Engineering for the Transportation Critical

InfrastructureThe Development of a Methodology and

Mathematical Model for Assessing the Impacts of K Links Disconnects have on Defined Links of the

Network

Page 2: Terms and Definitions

4Department of EMIS

SMU School of Engineering

Leadership in Engineering

• Critical Infrastructure (CI)

• System

• Transportation CI

• System of Systems (SoS)

• Major Cities

• City Boundary

• Network

Terms and Definitions

Page 3: Terms and Definitions

5Department of EMIS

SMU School of Engineering

Leadership in Engineering

• Movement of Goods

• Trucks

• Peak Traffic

• Normal Traffic

• Other Traffic

• Days of Operation

Terms and Definitions

Page 4: Terms and Definitions

6Department of EMIS

SMU School of Engineering

Leadership in Engineering

• Node• Arc Link• Disconnect• Steady State• Highway • Defined Links• Worst Link• Best Link

Terms and Definitions

Page 5: Terms and Definitions

7Department of EMIS

SMU School of Engineering

Leadership in Engineering

Objective

• The objective of this dissertation is to develop a methodology, using a SE approach, and apply the methodology to develop a mathematical model, using performance metrics such as travel time and flow, to simulate the impacts K Links disconnects have on highway networks of major metropolitan cities

Page 6: Terms and Definitions

8Department of EMIS

SMU School of Engineering

Leadership in Engineering

Objective

– Two Objective Steps

1. Systems Engineering Approach

2. K Links with Highest Affect on Network

Page 7: Terms and Definitions

9Department of EMIS

SMU School of Engineering

Leadership in Engineering

Research Significance

• Contribution: This dissertation provides officials a decision-making methodology and tool for resource allocation and risk mitigation– Metrics that measure the performance of the

network given disconnects occurring– Ranking of K Links affecting the network the most

Page 8: Terms and Definitions

10Department of EMIS

SMU School of Engineering

Leadership in Engineering

Research Significance

• Decision Making Methodology and Tool

i, j

Page 9: Terms and Definitions

11Department of EMIS

SMU School of Engineering

Leadership in Engineering

Research Significance

• Algorithm for finding efficiently the K Links with the greatest impact on the network

Minutes

Acc

urac

y

Accuracy Vs. Time

Page 10: Terms and Definitions

12Department of EMIS

SMU School of Engineering

Leadership in Engineering

Brief Literature Review

• SE– Osmundson et al, The Journal of The International Council on Systems

Engineering (INCOSE), 2004

– Tahan et al, The Journal of The INCOSE, 2005

– Bahill et al, The Journal of The INCOSE, 2005

– Blanchard et al, “Stems Engineering and Analysis”, 1990

– INCOSE, “Systems Engineering Handbook”, 2004

– Hazelrigg, “Sys. Eng.: An Approach to Information-Based Design” 1996

– Miller et al, “Systems Engineering Management”, 2002

– Stock et al, “Strategic Logistics Management”, 1993

– Ibarra et al, Conference for Systems Engineering, 2005

– Blanchard, “Logistics Engineering and Management”, 2004

– US Department of Homeland Security, “Budget in Brief, Fiscal Year 2005”

Page 11: Terms and Definitions

13Department of EMIS

SMU School of Engineering

Leadership in Engineering

Brief Literature Review

• Modeling– Osmundson et al, The Journal of The International Council on Systems

Engineering (INCOSE), 2004

– Bahill et al, The Journal of The INCOSE, 2005

– Sathe et al, Transportation Research Board, 2005

– Jain et al, Transportation Science, 1997

– Arroyo et al, Transportation Research Board, 2005

– Rardin, “Optimizations in Operations Research”, 1998

– Rinaldi et al, IEEE Control System Magazine. 2001

– Murray-Tuite, Dissertation, 2003

Page 12: Terms and Definitions

14Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering Process• Defining the System – System of Systems

AgricultureWater

Public Health

EmergencyServices

DefenseIndustrial

Base

Telecom.

EnergyTransportation

Government

Chemical andHazMat

Postal andShipping

Banking andFinance

FoodAgriculture

Water

Public Health

EmergencyServices

DefenseIndustrial

Base

Telecom.

EnergyTransportation

Government

Chemical andHazMat

Postal andShipping

Banking andFinance

Food

Page 13: Terms and Definitions

15Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering Process

• Need Analysis

• Stakeholders• City• State and Federal• Business• Society (Indirectly)

Page 14: Terms and Definitions

16Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering Process

• Requirements– Mission Definition– Performance and Physical Parameters– Use Requirements

Page 15: Terms and Definitions

17Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering ProcessC

ompo

nent

s

• Transportation CI SoS

INPUT•Disconnects•Hrs of Op.

PROCESS•Mathematical model

Att

ribu

tes

•Flow•Distance

•Links •Nodes•Efficiency of model

RelationshipsMovement of Goods

Efficiently Finding K Links

Perf. of Defined

Links

OUTPUT•Performance

•Disconnects•Hours of operation

Page 16: Terms and Definitions

18Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering Process

• Ground Rules and Assumptions – Highway– Major Cities– Steady State

• Non-Event Days

• Construction established and on-going

• Mon – Fri

– Disconnect

Page 17: Terms and Definitions

19Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering Process

• Metrics– Performance of Network

• Travel Time

• Throughput

– Solution – Processing Time of Model (as a function of OD table and network topology)

(OD)

Links

Model /Algorithm

Time

Accuracy

Page 18: Terms and Definitions

20Department of EMIS

SMU School of Engineering

Leadership in Engineering

The Systems Engineering ProcessSystem

Requirements

SystemSolution

Validate &Verify

Actual Model

System Objective

City Boundary

Section of City

Small Network Enumeration

EnumerationProcessing Time

Functional Analysis

EnumerationProcessing Time

Page 19: Terms and Definitions

21Department of EMIS

SMU School of Engineering

Leadership in Engineering

Model

• Most naive process– Disconnect Link (Li,j) subject to Time (tn)

– Simulate Network Performance

– Connect Link (Li,j)

– Repeat until all links tested

Page 20: Terms and Definitions

22Department of EMIS

SMU School of Engineering

Leadership in Engineering

Model

• Objective– Performance of Network based on Defined Links

• Constraints– Mathematical model of how the system responds

to changes in variables

• Variables– Time of Day– Disconnected Links

Page 21: Terms and Definitions

23Department of EMIS

SMU School of Engineering

Leadership in Engineering

Example of Model

Time

1

2

a

i

b c

3

4

6

5

3

4

8

6

4

3

O D Matrix3 4

1 200 1002 200 200

Number of Vehicles traveling from Origin to Destination during Off-Peak Period

Page 22: Terms and Definitions

24Department of EMIS

SMU School of Engineering

Leadership in Engineering

1

2

a

i

b c

3

4

6, 300

5, 4004, 250

8, 450

6, 700

4, 400

3, 300

3, 450

Example of Model: Routing Assignment

Time, Flow

a i b c 3 4 a i b c 3 41 300 1 62 400 2 5a 450 250 a 3 4i 450 i 8b 700 b 6c 400 300 c 4 3

Flow = Veh / Hr Travel Time = Minutesq t

Page 23: Terms and Definitions

25Department of EMIS

SMU School of Engineering

Leadership in Engineering

1

2

a

i

b c

3

4

6, 300

5, 400

8, 700

6, 700

4, 400

3, 300

3, 700

Example of Model: Effects of Disconnect on Link (a,b)

Time, Flow

qa i b c 3 4

1 3002 400a 700 0i 700b 700c 400 300

Flow = Veh / Hr 1,3 = {1,a a,i i,b b,c c,3} = 271,3 = {1,a a,b b,c c,3} = 201,4 = {1,a a,i i,b b,c c,4} = 261,4 = {1,a a,b b,c c,4} = 192,4 = {1,a a,i i,b b,c c,3} = 262,3 = {1,a a,b b,c c,3} = 192,4 = {1,a a,i i,b b,c c,4} = 252,4 = {1,a a,b b,c c,4} = 18

Avg. T = 2.5Min/Veh

Page 24: Terms and Definitions

26Department of EMIS

SMU School of Engineering

Leadership in Engineering

Example of Model

1

2

a

i

b c

3

4

6, 300

5, 4006, 700

4, 400

3, 300

1

2

a

i

b c

3

4

6, 300

5, 400

8, 4503, 450

4, 700

1

2

a

i

b c

3

4

6, 300

5, 4006, 700

4, 400

3, 3004, 700

4, 250

Page 25: Terms and Definitions

27Department of EMIS

SMU School of Engineering

Leadership in Engineering

0.0

100.0

200.0

300.0

400.0

500.0

System

System 412.2 268.0 479.6 383.8 402.5

Link a Link b Link c Link d Link e

DefinedLinks Link a Link b Link c Link d Link eLink 1 17.2 25.1 35.0 72.0 19.1Link 2 74.0 36.3 93.4 19.8 15.6Link 3 22.2 17.4 28.8 0.5 97.4Link 4 37.1 74.2 32.0 29.7 28.0Link 5 90.7 9.3 95.5 98.1 60.7Link 6 28.9 32.9 82.7 61.7 54.8Link 7 75.1 23.1 1.2 14.9 13.2Link 8 43.1 33.8 64.5 18.4 60.3Link 9 23.9 16.0 46.4 68.9 53.4System 412.2 268.0 479.6 383.8 402.5

Links in Network

Example of Model: Performance for a General Metric

OUTPUTS

Sum of Performance

, …,

Page 26: Terms and Definitions

28Department of EMIS

SMU School of Engineering

Leadership in Engineering

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0

500.0

(2, 11) (1, 11) (2, 12) (3, 14) (1, 12) (4, 7) (5, 6) (3, 8) (4, 8) (2, 5) (3, 8) (1, 2) (3, 5) (2, 4) (4, 5) (5, 8)

Example of Model

Links

Perf

orm

ance

Worst

Best

OUTPUTS

0 is threshold

K Links = {2,11}, …, {1,12}affecting the TransportationCI the most

Page 27: Terms and Definitions

29Department of EMIS

SMU School of Engineering

Leadership in Engineering

OutputPerformance:•Travel Time/Throughput

I35W I35E I45

I35W I35E Hwy 75

I20

I30

I20

InputSingle Disconnect; 1/0

Variables•Temporal Time of Day: I =1, 2, 3 (peak, norm, other)•Links: l =(i,j), [(i+1), (j+1)],…, (i+n, j+n)

L1 L2 L3

L8 L7 L6

L5

L4

L9

Information Flow

I=1

I=1

Network

Page 28: Terms and Definitions

30Department of EMIS

SMU School of Engineering

Leadership in Engineering

• Restricting the Search Space– Find least reliable links

– Find largest/lightest flow

• Approximation Methods– “Quickly” find “Good” solution

Ideas for Improving Algorithmic Model Efficiencies

1

2

a

i

b c

3

4

6, 300

5, 4004, 250

8, 450

6, 700

4, 400

3, 300

3, 450

Page 29: Terms and Definitions

31Department of EMIS

SMU School of Engineering

Leadership in Engineering

Validation and Verification

• SE Approach– Integrations Process– V-Chart

• Model– Small Network– Enumeration– Efficiency of Model

Page 30: Terms and Definitions

32Department of EMIS

SMU School of Engineering

Leadership in Engineering

Conclusion

• Transportation CI is important– To individuals’ way of life – To companies’ way of doing business

• Proposed a Methodology and Mathematical Model to Determine Impact of K Links Disconnects have on the Defined Links of a Network

Page 31: Terms and Definitions

33Department of EMIS

SMU School of Engineering

Leadership in Engineering

Conclusion

• Research Significance– Society: A Methodology and Tool for Officials to

use in the Decision Making Process– Engineering: A New Algorithm for Solving

Complex Systems Efficiently