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RR (miles) WR (miles) 2 4 6 8 10 0 0 2 4 6 8 10 Figure 1. Initial development of a two-variable graph for the road construction problem, with the miles of rocked roads to be built on the Y-axis, and the amount of woods roads to be built on the X-axis.

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Figure 1. Initial development of a two-variable graph for the road construction problem, with the miles of rocked roads to be built on the Y-axis, and the amount of woods roads to be built on the X-axis. 10. 8. 6. RR (miles). 4. 2. 0. 0. 2. 4. 6. 8. 10. WR (miles). - PowerPoint PPT Presentation

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Page 1: RR (miles)

RR(miles)

WR(miles)

2 4 6 8 1000

2

4

6

8

10

Figure 1. Initial development of a two-variable graph for the road construction problem, with the miles of rocked roads to be built on the Y-axis, and the amount of woods roads to be built on the X-axis.

Page 2: RR (miles)

RR(miles)

WR(miles)

2 4 6 8 1000

2

4

6

8

10

30,000 WR + 50,000 RR 300,000

Feasible region

Figure 2. The budget constraint for the road construction problem.

Page 3: RR (miles)

RR(miles)

WR(miles)

2 4 6 8 1000

2

4

6

8

10

30,000 WR + 50,000 RR 300,000

RR 1.5

RR 4

WR 2.5 WR 6

Figure 3. A graph of the entire set of constraints to the road construction problem, and the areas related to the constraints where solutions are feasible.

Page 4: RR (miles)

RR(miles)

WR(miles)

2 4 6 8 1000

2

4

6

8

10

RR + WR = 8

RR + WR = 4

Figure 4. Identification of the optimal solution to the road construction problem using a family of objective functions.

RR + WR = 8.4

Page 5: RR (miles)

DS(trees)

CS(trees)

400 800 1,200 1,600 2,00000

400

800

1,200

1,600

2,000

100 DS + 50 CS 80,000

DS 100

CS 250

DS 600

Figure 5. The graphed constraints to the snag development problem, and the identification of the feasible region (gray area).

Page 6: RR (miles)

DS(trees)

CS(trees)

400 800 1,200 1,600 2,00000

400

800

1,200

1,600

2,000

CS + DS = 1,500

Figure 6. The optimal solution to the snag development problem.

Page 7: RR (miles)

Logs(miles)

Boulders(miles)

5 10 15 20 2500

5

10

15

20

25

10,000 Logs + 21,000 Boulders 250,000

Logs 5

Boulders 2.5

Boulders 7.5

Figure 7. The constraints and feasible region (gray area) associated with the fish habitat problem.

Page 8: RR (miles)

Figure 8. Hurricane damage to a pine stand after Hurricane Katrinain 2005.

Page 9: RR (miles)

Figure 9. Identification of the feasible region and optimal solution to the hurricane clean-up problem of cost minimization using a family of objective functions.

200,000

600,000

1,000,000

800,000

400,000

CH 400,000

CPB 300,000

CPB 500,000

CH + CPB 1,000,000

CH ($)

CPB ($)

CH + CPB

0

0 200,000 400,000 600,000 800,000 1,000,000

Page 10: RR (miles)

Logs(miles)

Boulders(miles)

5 10 15 20 2500

5

10

15

20

25

10,000 Logs + 21,000 Boulders 250,000

Logs 5

Boulders 2.5

Boulders 7.5

Boulders + Logs 15

A

B

Figure 10. A modified fish habitat problem, with multiple optimal solutions.

Page 11: RR (miles)

Timbervolume

Wildlifehabitat

A

B

C

D

(Feasible region solutions)

Figure 11. An example of efficient, feasible, inefficient, and infeasible solutions to a broad timber harvest and wildlife habitat management problem.

Page 12: RR (miles)

(Figure for question 7)

Roads

Streams

Streams to be treated with logs or boulders