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Slides prepared by JOHN LOUCKS St. Edward’s University. Chapter 10 Transportation, Assignment, and Transshipment Problems. Transportation Problem Network Representation General LP Formulation. Transportation, Assignment, and Transshipment Problems. - PowerPoint PPT Presentation

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Page 1: Slides prepared by JOHN  LOUCKS St. Edward’s University

1 Slide

© 2006 Thomson South-Western. All Rights Reserved.

Slidesprepared by

JOHN LOUCKS

St. Edward’sUniversity

Page 2: Slides prepared by JOHN  LOUCKS St. Edward’s University

2 Slide

© 2006 Thomson South-Western. All Rights Reserved.

Chapter 10Transportation, Assignment,and Transshipment Problems

Transportation Problem• Network Representation• General LP Formulation

Page 3: Slides prepared by JOHN  LOUCKS St. Edward’s University

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© 2006 Thomson South-Western. All Rights Reserved.

Transportation, Assignment, and Transshipment Problems

A network model is one which can be represented by a set of nodes, a set of arcs, and functions (e.g. costs, supplies, demands, etc.) associated with the arcs and/or nodes.

Transportation, assignment, and transshipment problems of this chapter as well as the PERT/CPM problems (in another chapter) are all examples of network problems.

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© 2006 Thomson South-Western. All Rights Reserved.

Transportation, Assignment, and Transshipment Problems

Each of the three models of this chapter can be formulated as linear programs and solved by general purpose linear programming codes.

For each of the three models, if the right-hand side of the linear programming formulations are all integers, the optimal solution will be in terms of integer values for the decision variables.

However, there are many computer packages (including The Management Scientist) that contain separate computer codes for these models which take advantage of their network structure.

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© 2006 Thomson South-Western. All Rights Reserved.

Transportation Problem

The transportation problem seeks to minimize the total shipping costs of transporting goods from m origins (each with a supply si) to n destinations (each with a demand dj), when the unit shipping cost from an origin, i, to a destination, j, is cij.

The network representation for a transportation problem with two sources and three destinations is given on the next slide.

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Transportation Problem

Network Representation

2

c1

1 c12

c13c21

c22c23

d1

d2

d3

s1

s2

Sources Destinations

3

2

1

1

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© 2006 Thomson South-Western. All Rights Reserved.

Transportation Problem LP Formulation

The LP formulation in terms of the amounts shipped from the origins to the destinations, xij , can be written as:

Min cijxij i j s.t. xij < si for each origin i j xij = dj for each destination j i xij > 0 for all i and j

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© 2006 Thomson South-Western. All Rights Reserved.

LP Formulation Special CasesThe following special-case modifications

to the linear programming formulation can be made:• Minimum shipping guarantee from i to j:

xij > Lij

• Maximum route capacity from i to j: xij < Lij

• Unacceptable route: Remove the corresponding decision

variable.

Transportation Problem

Page 9: Slides prepared by JOHN  LOUCKS St. Edward’s University

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© 2006 Thomson South-Western. All Rights Reserved.

Example: Acme Block Co.

Acme Block Company has orders for 80 tons ofconcrete blocks at three suburban locationsas follows: Northwood -- 25 tons,Westwood -- 45 tons, andEastwood -- 10 tons. Acmehas two plants, each of whichcan produce 50 tons per week.Delivery cost per ton from each plantto each suburban location is shown on the next slide.

How should end of week shipments be made to fillthe above orders?

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© 2006 Thomson South-Western. All Rights Reserved.

Delivery Cost Per Ton

Northwood Westwood Eastwood Plant 1 24 30 40

Plant 2 30 40 42

Example: Acme Block Co.

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© 2006 Thomson South-Western. All Rights Reserved.

Partial Spreadsheet Showing Problem DataA B C D E F G H

12 Constraint X11 X12 X13 X21 X22 X23 RHS3 #1 1 1 1 504 #2 1 1 1 505 #3 1 1 256 #4 1 1 457 #5 1 1 108 Obj.Coefficients 24 30 40 30 40 42 30

LHS Coefficients

Example: Acme Block Co.

Page 12: Slides prepared by JOHN  LOUCKS St. Edward’s University

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© 2006 Thomson South-Western. All Rights Reserved.

Partial Spreadsheet Showing Optimal SolutionA B C D E F G

10 X11 X12 X13 X21 X22 X2311 Dec.Var.Values 5 45 0 20 0 1012 Minimized Total Shipping Cost 24901314 LHS RHS15 50 <= 5016 30 <= 5017 25 = 2518 45 = 4519 10 = 10E.Dem.

W.Dem.N.Dem.

ConstraintsP1.Cap.P2.Cap.

Example: Acme Block Co.

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© 2006 Thomson South-Western. All Rights Reserved.

Optimal Solution

From To Amount Cost

Plant 1 Northwood 5 120

Plant 1 Westwood 45 1,350

Plant 2 Northwood 20 600

Plant 2 Eastwood 10 420

Total Cost = $2,490

Example: Acme Block Co.

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Partial Sensitivity Report (first half)

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$C$12 X11 5 0 24 4 4$D$12 X12 45 0 30 4 1E+30$E$12 X13 0 4 40 1E+30 4$F$12 X21 20 0 30 4 4$G$12 X22 0 4 40 1E+30 4$H$12 X23 10.000 0.000 42 4 1E+30

Example: Acme Block Co.

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© 2006 Thomson South-Western. All Rights Reserved.

Partial Sensitivity Report (second half)

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$E$17 P2.Cap 30.0 0.0 50 1E+30 20$E$18 N.Dem 25.0 30.0 25 20 20$E$19 W.Dem 45.0 36.0 45 5 20$E$20 E.Dem 10.0 42.0 10 20 10$E$16 P1.Cap 50.0 -6.0 50 20 5

Example: Acme Block Co.

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End of Chapter 10