Facility Location

COB 300C – Fall 2002

Facility Location Facility Location is the placement of facility with respect to

customers, suppliers and other interacting facilities. It should consider:– Operating costs

– Customer convenience

– Transportation costs

– Access to key related services

such as banking and

educational opportunities

– Strategic factors

Location as a Strategic DecisionLocation as a Strategic Decision

1. Long-term commitment

2. Linked to customer base

3. Regional facility supplies specific area

4. Product facility supplies globally

5. Combination of regional and product facilities

Regional or Global

Factors Affecting theLocation Decision

Strategic nature of decision

Quantitative factors Government incentives Qualitative factors

Including theQualitative Factors

Integrate qualitative factors

– Determine which factors are relevant to the problem

– Weigh each factor

– Rate each site for each factor

Examples of Indianapolis and Lexington (Slide 1 of 2)

Indianapolis Lexington Weight Raw Score Raw Score

Recreational activities 20 8 7University research facilities 40 8 8Union activities 40 4 7Banking services 80 7 6Available labor pool 60 7 5

Examples of Indianapolis and Lexington (Slide 2 of 2)

Indianapolis Lexington

Weighted score Weighted score

Recreational activities 160 140 University research facilities 320 320Union activities 160 280Banking services 560 480Available labor pool 420 300

Total 1,620 1,520

Analyzing Spatial RelationshipsAnalyzing Spatial Relationships

Load-Distance Method measures proximity to customers, suppliers, interacting facilities

Transportation Problem relates to the cost of transporting materials to and from multiple facilities

Distance from Facilityto Customer

Health Care UnitLocation Problem

Locating a Health Care Center Using the “Load-Distance Method” (Slide 1 of 3)

Population coordinates

Code ai xi yi (ai )(xi) (ai)(yi)

10111 30,000 3 2 90,000 60,00010112 25,000 2 4 50,000 100,00010113 11,000 1.5 5.5 16,500 60,50010114 8,000 3 7 24,000 56,00010115 18,000 3.5 5 63,000 90,00010116 24,000 4.5 3.5 108,000 84,00010117 12,000 5.25 6.25 63,000 75,000

Total 128,000 414,500 525,500

Zip

Locating a Health Care Center Using the “Load-Distance Method” (Slide 2 of 3)

where xf = Distance along the x axis from the origin to the center of gravity yf = Distance along the y axis from the origin to the center of gravity ai = The activity level (load) from the i th location to the proposed facility Xi = the coordinate on the x axis for the i th customer location yi = the coordinate on the y axis for the i th customer location

n

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Locating a Health Care Center Using the “Load-Distance Method” (Slide 3 of 3)

The coordinates of the center of gravity are:

xf = yf = 414,500 525,500

128,000 128,000

= 3.24 = 4.11

Transportation Problem

Cost of moving materials between multiple destinations

Vogel’s Approximation Method

To evaluate two locations, solve the transportation problem for each location

OR

Transportation Example

New facility capacity = 5000 units/month We must choose either Des Moines, Iowa or

Montgomery, Alabama Transportation costs per unit for Des Moines

and Montgomery to each customer location are provided

We are interested in total transportation cost for Des Moines versus Montgomery

Transportation Example (cont’d)

Supply

Lexington - 12,420

Milan - 9,380

DesMoines - 5,000 (proposed)

or

Montgomery - 5,000 (proposed)

Transportation Example (cont’d)

Demand

Baton Rouge - 6,740

Bismarck - 8,400

Tampa - 5,050

Youngstown - 5,670

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420Lexington

17 15 17 9 0 9380Milan

17 11 19 14 0 5000

DesMoines

6740 8400 5050 5670 940 26800DEMAND

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 12Lexington

17 15 17 9 0 9380 9Milan

17 11 19 14 0 5000 11DesMoines

6740 8400 5050 5670 940 26800DEMAND

3 4 1 3 0

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 12Lexington 940

17 15 17 9 0 9380 9Milan

17 11 19 14 0 5000 11DesMoines

6740 8400 5050 5670 940 26800DEMAND

3 4 1 3 0

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 940 11480

17 15 17 9 0 9380 6Milan

17 11 19 14 0 5000 3DesMoines

6740 8400 5050 5670 940 26800DEMAND 0

3 4 1 3

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 940 11480

17 15 17 9 0 9380 6Milan 5670

17 11 19 14 0 5000 3DesMoines

6740 8400 5050 5670 940 26800DEMAND 0

3 4 1 3

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 940 11480

17 15 17 9 0 9380 2Milan 5670 3710

17 11 19 14 0 5000 6DesMoines

6740 8400 5050 5670 940 26800DEMAND 0 0

3 4 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 940 11480

17 15 17 9 0 9380 2Milan 5670 3710

17 11 19 14 0 5000 6DesMoines 5000

6740 8400 5050 5670 940 26800DEMAND 0 0

3 4 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 940 11480

17 15 17 9 0 9380 2Milan 5670 3710

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 3400 0 0

3 3 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 6740 940 11480

17 15 17 9 0 9380 2Milan 5670 3710

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 3400 0 0

3 3 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 6740 940 4740

17 15 17 9 0 9380 2Milan 5670 3710

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 3400 0 0

3 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 2Lexington 6740 940 4740

17 15 17 9 0 9380 2Milan 3400 5670 3710

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 3400 0 0

3 1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 Lexington 6740 940 4740

17 15 17 9 0 9380 Milan 3400 5670 310

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 0 0 0

1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 Lexington 6740 4740 940 4740

17 15 17 9 0 9380 Milan 3400 5670 310

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 0 0 0

1

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 Lexington 6740 4740 940 0

17 15 17 9 0 9380 Milan 3400 5670 310

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 0 310 0 0

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 Lexington 6740 4740 940 0

17 15 17 9 0 9380 Milan 3400 310 5670 310

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 0 310 0 0

DESTINATION

Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE

14 18 16 12 0 12420 Lexington 6740 4740 940 0

17 15 17 9 0 9380 Milan 3400 310 5670 0

17 11 19 14 0 5000 DesMoines 5000 0

6740 8400 5050 5670 940 26800DEMAND 0 0 0 0 0

Total Transportation Cost for Des Moines6740($14)+4740($16)+940($0)+3400($15)+

310($17)+5670($9)+5000($11) = $332,500

For Next Class Figure Transportation Cost for Montgomery

Which is best choice based on Vogel’s Approximation?

Are there other factors to consider? Montgomery’s Transportation Costs:

– Montgomery to Baton Rouge: $9 per unit– Montgomery to Bismarck: $19 per unit– Montgomery to Tampa: $12 per unit– Montgomery to Youngstown $15 per unit

Location Example - Load Distance Location of a warehouse in Germany Method: Load-Distance Method (a.k.a.:

center-of-gravity method) Customer locations (coordinates) and

demands in units per year are given

CITY Demand ai (units/yr.) Xi Yi

Hamburg 42,000 3.25 7Cologne 22,000 1 4.5Stuttgart 37,000 2.5 2Munich 66,000 4.25 1.25Dresden 45,000 5.75 4.5Berlin 113,000 5.5 6

CITY Demand ai (units/yr.) Xi Yi (ai)(xi) (ai)(yi)

Hamburg 42,000 3.25 7 136,500 294,000 Cologne 22,000 1 4.5 22,000 99,000 Stuttgart 37,000 2.5 2 92,500 74,000 Munich 66,000 4.25 1.25 280,500 82,500 Dresden 45,000 5.75 4.5 258,750 202,500 Berlin 113,000 5.5 6 621,500 678,000

CITY Demand ai (units/yr.) Xi Yi (ai)(xi) (ai)(yi)

Hamburg 42,000 3.25 7 136,500 294,000 Cologne 22,000 1 4.5 22,000 99,000 Stuttgart 37,000 2.5 2 92,500 74,000 Munich 66,000 4.25 1.25 280,500 82,500 Dresden 45,000 5.75 4.5 258,750 202,500 Berlin 113,000 5.5 6 621,500 678,000

TOTAL 325,000 1,411,750 1,430,000

xf =(a )(x )

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yf =(a )(y )

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i=1

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1 411 750

325 0004 34

1 430 000

325 0004 40

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Show map here

Location?

Central Germany

Other Factors to Consider?

operating costs required investment government incentives qualitative factors overall strategy of organization

Location Decision Affects Other Operating Decisions

Alternative to on-site expansion

On-site expansion is problematic– Material handling and storage

– Complex production flow

– Strained communication

– New technology delayed

– Use of old equipment

– Layering of expanded responsibilities

International Dimensions ofLocation Decision

Reasons for locating in foreign countries

– Comparative Advantage

– Closeness to market

– Political relationships

– Availability of resources

Location Analysis forLocation Analysis forService OperationsService Operations

Concepts and techniques discussed so far apply to service operations

Service issues:» Minimize response time:

Emergency medical services

» Provide minimum coverage: Fire Protection

» Mobile location: Police or security units