5
Network Design in
the Supply Chain
PowerPoint presentation to accompany
Chopra and Meindl Supply Chain Management, 5e
Global Edition
Copyright ©2013 Pearson Education.
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Learning Objectives
1. Understand the role of network design in a
supply chain.
2. Identify factors influencing supply chain
network design decisions.
3. Develop a framework for making network
design decisions.
4. Use optimization for facility location and
capacity allocation decisions.
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Network Design Decisions
• Facility role
– What role, what processes?
• Facility location
– Where should facilities be located?
• Capacity allocation
– How much capacity at each facility?
• Market and supply allocation
– What markets? Which supply sources?
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Factors Influencing
Network Design Decisions
• Strategic factors
• Technological factors
• Macroeconomic factors
– Tariffs and tax incentives
– Exchange-rate and demand risk
– Freight and fuel costs
• Political
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Factors Influencing
Network Design Decisions
• Infrastructure factors
• Competitive factors
– Positive externalities between firms
– Locating to split the market
• Customer response time and local
•
presence
Logistics and facility costs
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Strategic Roles of a Facility
• Offshore facility: Low cost facility for export
production
• Source Facility: Low cost facility for global
production
• Server Facility: Regional Production Facility
• Contributor Facility: Regional Production Facility
with Development Skills
• Outpost Facility: Regional Production Facility
built to gain local skills
• Lead Facility: Facility that leads in development
and process technologies
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Technological Factors
• Characteristics of available production
technologies have a significant impact on the
network design:
– If production technology provide significant
economies of scale, few high capacity locations are
the most effective
– If facilities have lower fixed costs, many local facilities
are preferred.
• Flexibility of the production technology impacts
the degree of consolidation in the network:
– If the production technology is inflexible, build many
local facilities
– Else, build few but large facilities
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Macroeconomic Factors
• Tariffs and tax incentives
– Tariffs: Any duties that must be paid when
product, equipment are moved across an
international, state or city boundry.
– Developing countries have free trade zones
• Exchange rate and demand risk
– Valuable TRL and textile industry in Turkey
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Infrastructure Factors
• Availability of sites
• Availability of labor
• Proximity to transportation terminals,
•
•
•
railservice, airports, seaports,
Highway access
Congestion
Local utilities
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Competitive Factors
• Positive externalities between firms
– Ex: Gas stations and retail shops
Auto Repair Districts
• Locating to Split the market
– When firms do not control price, but compete
on distance from the customer, they can
maximize market share by locating close to
each other and splitting the market
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Ex:Locating to Split the Market
•
Let there be two firms located
at points a and 1-b on a line
segment between 0 and 1. Let
the customers be located
uniformly on this line.
If the total demand is 1, the
demand at the two firms is
maximized when a=b=1/2.
Thus both firms maximize their
market share when they move
closer to each other, although
the average distance travelled
is greater than the seperate
case.
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0
a
1-b
1
a 1 b
2
a 1 b
1 b  a
d1 
, d2 
2
2
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Framework for Network Design
Decisions
Figure 5-2
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Framework for Network Design
Decisions
• Phase I: Define a Supply Chain
Strategy/Design
– Clear definition of the firm’s competitive
strategy
– Forecast the likely evolution of global
competition
– Identify constraints on available capital
– Determine growth strategy
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Framework for Network Design
Decisions
• Phase II: Define the Regional Facility
Configuration
– Approx. no. of facilities, regions where facilities will be
set up, whether a facility will produce all products of a
given market, etc
– Forecast of the demand by country or region
– Economies of scale or scope
– Identify demand risk, exchange-rate risk, political risk,
tariffs, requirements for local production, tax
incentives, and export or import restrictions
– Identify competitors
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Framework for Network Design
Decisions
• Phase III: Select a Set of Desirable
Potential Sites
– Hard infrastructure requirements
– Soft infrastructure requirements
• Phase IV: Location Choices
–Select a precise location and capacity
allocation for each facility
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Models for Facility Location and Capacity
Allocation
• Goal is to maximize the overall profitability while
•
providing the appropriate responsiveness.
Managers use network design models in two
different ways:
– Decide on locations and capacities of facilities
– Decide on the market share of each facility and
identify lanes of transportation
• Models are two types:
– Network optimization models
– Gravity models
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Models for Facility Location and
Capacity Allocation
• Important information
–
–
–
–
–
–
–
–
–
Location of supply sources and markets
Location of potential facility sites
Demand forecast by market
Facility, labor, and material costs by site
Transportation costs between each pair of sites
Inventory costs by site and as a function of quantity
Sale price of product in different regions
Taxes and tariffs
Desired response time and other service factors
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Phase II: Capacitated Plant
Location Model
n = number of potential plant locations/capacity
m = number of markets or demand points
D j = annual demand from market j
yi = 1 if plant i is open, 0 otherwise
xij = quantity shipped from plant i
to market j
K i = potential capacity of plant i
f i = annualized fixed cost of keeping plant i open
cij = cost of producing and shipping one unit from plant i to market j (cost
includes production, inventory, transportation, and tariffs)
n
n
Min f i yi  
i 1
x
ij
m
x
j 1
c x
j 1
subject to
n
i 1
i 1
m
ij
 D j for j  1,..., m
 K i yi for i  1,..., n
ij ij
Problem:
There are several options
to meet the demand
-construct a small facility
in each region to lower
total transportation cost
-construct a large facility to
lower the total construction
cost
yi  0,1 and x ij  0, for i  1,..., n; j  1,..., m
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Capacitated Plant Location Model
Sun Oil Company
•
Figure 5-4
Vice president of Supply Chain decides to view the worldwide demand in
five regions: North America, South America, Europe, Asia, Africa
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Capacitated Plant Location Model
Figure 5-5
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Capacitated Plant Location Model
Figure 5-5
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Capacitated Plant Location Model
Figure 5-6
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Capacitated Plant Location Model
Figure 5-7
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Phase III:Gravity Location Model
Consider the problem of locating a new facility among k facilities in supply chain.
Where should it be located, i.e., the what should be the (x,y) coordinates of this
new location?
xn, yn: coordinate location of either a market or supply source n=1,2,...k
Fn: cost of shipping one unit for one mile between the facility and either
market or supply source n
Dn: quantity to be shipped between facility and market or supply source n
(x, y) is the location selected for the facility, the distance dn between
the facility at location (x, y) and the supply source or market n is given
by
dn =
(x – x ) + ( y – y )
2
n
Total transportation
cost to minimize
= 𝑇𝐶 =
2
n
𝑘
𝑑𝑛 𝐷𝑛 𝐹𝑛
𝑛=1
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Gravity Location Model
Transportation Cost
$/Ton Mile (Fn)
Quantity in Tons
(Dn)
Buffalo
0.90
Memphis
St. Louis
Sources/Markets
Coordinates
xn
yn
500
700
1,200
0.95
300
250
600
0.85
700
225
825
Atlanta
1.50
225
600
500
Boston
1.50
150
1,050
1,200
Jacksonville
1.50
250
800
300
Philadelphia
1.50
175
925
975
New York
1.50
300
1,000
1,080
Supply sources
Markets
Total transportation cost TC =
k
åd D F
n
n
Table 5-1
n
n=1
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Gravity Location Model
Figure 5-8
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Gravity Location Model
Figure 5-8
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Gravity Location Model
The gravity model can also be solved using the following
iterative procedure:
1. For each supply source or market n, evaluate dn
2. Obtain a new location (x’, y’) for the facility, where
k
x¢ =
Dn Fn xn
å d
n=1
n
k
Dn Fn
å d
n=1
n
k
and y¢ =
Dn Fn yn
å d
n=1
n
k
Dn Fn
å d
n=1
n
3. If the new location (x’ , y’ ) is almost the same as
(x, y) stop. Otherwise, set (x, y) = (x’ , y’ ) and go to
step 1
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Phase IV: Network Optimization
Models
Supply
City
Demand City
Production and Transportation Cost
per Thousand Units (Thousand $)
Monthly
Capacity
(Thousand
Units) K
Monthly
Fixed Cost
(Thousand
$) f
Atlanta
Boston
Chicago
Denver
Omaha
Portland
Baltimore
1,675
400
985
1,630
1,160
2,800
18
7,650
Cheyenne
1,460
1,940
970
100
495
1,200
24
3,500
Salt Lake
City
1,925
2,400
1,450
500
950
800
27
5,000
Memphis
380
1,355
543
1,045
665
2,321
22
4,100
Wichita
922
1,646
700
508
311
1,797
31
2,200
10
8
14
6
7
11
Monthly
demand
(thousand
units) Dj
TelecomOne: capacity 71,000 units/month; demand 32,000 units/monthTable 5-2
HighOptic: capacity 51,000 units/month; demand 24,000 units/month
Producers of fiberoptic telecommunications equipment
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Network Optimization Models
• Allocating demand to production facilities
n
m
= number of factory locations (3 or 2)
xij
= number of markets or demand points (3 or 3)
= quantity shipped from factory i
to market j
Dj
= annual demand from market j
Ki
= capacity of factory i
cij
= cost of producing and shipping one unit from factory i to market j
n
n
x
m
Min cij xij
i 1 j 1
subject to
i 1
ij
m
x
j 1
ij
 D j for j  1,..., m
 K i for i  1,..., n
Problem: Decide how markets are allocated to the facilities. Response time
should be considered.
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Network Optimization Models
• Optimal demand allocation
TelecomOne
HighOptic
Atlanta
Boston
Chicago
Denver
Omaha
Portland
Baltimore
0
8
2
Memphis
10
0
12
Wichita
0
0
0
Salt Lake
0
0
11
Cheyenne
6
7
0
Solve seperately:
TelecomOne
Variable cost=$14,886,000
Fixed cost=$13,950,000
Total cost=$ 28,836,000
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Table 5-3
HighOptic
Variable cost=$12,865,000
Fixed cost=$8,500,000
Total cost=$ 21,365,000
Total Cost
=$50,201,000
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Capacitated Plant Location Model
• Merge the companies as TelecomOptic
• Response time?
• Solve using location-specific costs
yi =
xij =
1 if factory i is open, 0 otherwise i  1,2,...,5; j  1,2,...,6
quantity shipped from factory i to market j
n
n
Min f i yi  
i 1
x
m
c x
j 1
ij
 D j for j  1,..., m
 xij  K i yi for i  1,..., n
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j 1
ij ij
subject to
n
i 1
i 1
m
yi  0,1 and x ij  0
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Capacitated Plant Location Model
Figure 5-9
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Capacitated Plant Location Model
Figure 5-10
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Capacitated Plant Location Model
Figure 5-10
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Capacitated Plant Location Model
Figure 5-11
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5-36
Capacitated Model With
Single Sourcing
Close the plants
in Salt Lake and
Wichita
Optimal total cost: $47,401,000
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Figure 5-12
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Capacitated Model With
Single Sourcing
•
•
•
Each market is supplied by only one factory
Lower complexity and less flexibility requirement from each facility
Modify decision variables
yi = 1 if factory i is open, 0 otherwise
xij = 1 if market j is supplied by factory i, 0 otherwise
n
n
m
Minå f i yi + å å D j cij xij
i=1
i=1 j=1
subject to
n
åx
ij
= 1 for j = 1,...,m
i=1
m
åD x
i ij
£ K i yi for i = 1,...,n
j=1
xij , yi Î {0,1}
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Capacitated Model With
Single Sourcing
• Optimal network configuration with single
sourcing
Open/
Closed
Atlanta
Boston
Chicago
Denver
Omaha
Portland
Baltimore
Closed
0
0
0
0
0
0
Cheyenne
Closed
0
0
0
0
0
0
Salt Lake
Open
0
0
0
6
0
11
Memphis
Open
10
8
0
0
0
0
Wichita
Open
0
0
14
0
7
0
Table 5-4
Optimal total cost: $49,717,000
$2.3million higher than the merged case!
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Locating Plants and Warehouses
Simultaneously
Figure 5-13
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5-40
Locating Plants and Warehouses
Simultaneously
• Model inputs
m
n
l
t
Dj
Ki
Sh
We
Fi
fe
chi
cie
cej
=
=
=
=
=
=
=
=
=
=
=
=
=
number of markets or demand points
number of potential factory locations
number of suppliers
number of potential warehouse locations
annual demand from customer j
potential capacity of factory at site i
supply capacity at supplier h
potential warehouse capacity at site e
fixed cost of locating a plant at site i
fixed cost of locating a warehouse at site e
cost of shipping one unit from supply source h to factory i
cost of producing and shipping one unit from factory i to warehouse e
cost of shipping one unit from warehouse e to customer j
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Locating Plants and Warehouses
Simultaneously
• Goal is to identify plant and warehouse locations
and quantities shipped that minimize the total
fixed and variable costs
Yi
Ye
xej
xie
xhi
=
=
=
=
=
1 if factory is located at site i, 0 otherwise
1 if warehouse is located at site e, 0 otherwise
quantity shipped from warehouse e to market j
quantity shipped from factory at site i to warehouse e
quantity shipped from supplier h to factory at site i
n
t
i=1
e=1
l
n
t
m
Minå Fi yi + å f e ye + å å chi xie + å å cej xej
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h=1 i=1
e=1 j=1
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Locating Plants and Warehouses
Simultaneously
subject to
n
åx
hi
£ Sh for h = 1,...,l
i=1
m
åx
ej
£ We ye for e = 1,...,t
j=1
l
åx
t
hi
– å xie ³ 0 for i = 1,...,n
h=1
e=1
t
åx
ie
e=1
m
åx – åx
ie
i=1
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åx
ej
= D j for j = 1,...,m
e=1
£ Ki yi for i = 1,...,n
n
t
ej
yi , ye Î {0,1},xej ,xie ,xhi ³ 0
³ 0 for e = 1,...,t
j=1
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Accounting for Taxes, Tariffs, and
Customer Requirements
• A supply chain network should maximize profits
•
after tariffs and taxes while meeting customer
service requirements
Modified objective and constraint
m
n
n
j=1
i=1
i=1
n
m
Maxå rj å xij – å Fi yi – å å cij xij
n
åx
ij
i=1 j=1
£ D j for j = 1,...,m
i=1
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5-44
Making Network Design Decisions
In Practice
• Do not underestimate the life span of
•
•
•
facilities
Do not gloss over the cultural
implications
Do not ignore quality-of-life issues
Focus on tariffs and tax incentives
when locating facilities
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Summary of Learning Objectives
1. Understand the role of network design
in a supply chain
2. Identify factors influencing supply
chain network design decisions
3. Develop a framework for making
network design decisions
4. Use optimization for facility location
and capacity allocation decisions
Copyright ©2013 Pearson Education.
5-46
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