Members:
1. MOHD AQHAIRI BIN BAHARI
2. LAW MEI LIN
3. AZMI BIN HASSAN
4. MOHD NAZIH BIN JAAFAR
B050810175
B050810007
B050810064
B050810237
1
7.5 Transportation Method
7.5.1 Introduction to Transportation Problem
7.5.2 The Greedy Heuristic
7.5.3 Solving Transportation Problems with Linear
Programming
7.5.4 Generalizations of the Transportation Problem
7.5.4.1 Infeasible Routes
7.5.4.2 Unbalanced Problems
7.5.6 More General Network Formulations
2
Transportation Problem
 Is a mathematical model for optimally scheduling the
flow of goods from production facilities to distribution
centers.
Plants
Warehouses
 Ex:
3
 Assumptions:
Fixed amount of product is transported from a group
of sources (plants) to a group of sinks (warehouses).
2. The unit cost of transporting from each source to
each sink is known.
1.
 Goals:
Find the optimal flow paths
2. Amounts to be shipped to minimize the total cost of
all shipments.
1.
4
Example 1:
 The Pear Disk Drive Corporation produces several capacities of Winchester
drives for personal computers. In 1999, Pear produced drives with
capacities from 20 to 160 gigabytes (GB), all in the 3.5 –inch form factor.
The most popular product is the 80-GB drive, which is sold to several
computer manufacturers. Pear produces the drives in three plants located in
Sunnyvale, California; Dublin, Ireland; and Bangkok, Thailand.
Periodically, the shipments are made from these three production facilities
to four distribution warehouses located in the United States in Amarillo,
Texas; Teaneck, New Jersey; Chicago, Illinois; and Sioux Falls, South
Dakota. Over the next month, it has been determined that these warehouses
should receive the following proportions of the company’s total production
of the 80-GB drives:
Warehouse
Amarillo
Teaneck
Chicago
Sioux Falls
Percentage of Total Production
31
30
18
21
5
 The production quantities at the factories in the next
month are expected to be (in thousands of units)
Plant
Sunnyvale
Dublin
Bangkok
Anticipated Production
(in 1000s of units)
45
120
95
 Since the total production at the three plants is 260
units, the amount shipped to the four warehouses will
be (roundded to the nearest unit)
Warehouse
Amarillo
Teaneck
Chicago
Sioux Falls
Total Shipment Quantity
(1000s)
80
78
47
55
6
Shipping costs per 1,000 Units in RM
F
R
O
M
Amarillo
Sunnyvale 250
Dublin
1280
Bangkok
1550
TO
Teaneck
420
990
1420
Chicago
380
1440
1660
Sioux Falls
280
1520
1730
Unforseen problems:
1. Forced shutdown at a plant
2. Unanticipated swings in the regional
demand
3. Poor weather along some routes
7
The Greedy Heuristic
 Constructing a transportation tableau.
8
9
 Solution:
Let xij be the amount of flow from source i to sink j,
x11 = 45,
x23 = 7,
x21 = 35,
x33 = 40,
x22 = 78,
x34 = 55,
other xij = 0
 The total cost for this solution is
(45)(250) + (35)(1280) + …. = RM 304,900
10
Solving Transportation Problems
with Linear Programming
 Let m be the number of sources
 Let n be the number of sinks
xij = flow from source i to sink j
for 1 i  m and 1 j  n
cij = cost of shipping one unit from i to j
m
 Total cost of all shipments:
n
 cij xij
i 1 j 1
11
 Constraints:
Total amount shipped out of each source equals the
amount available at that source
2. The amount shipped into any sink equals the amount
required at that sink.
1.
12
Let ai be the total amount to be shipped out of source i
Let bj be the total amount to be shipped into sink
n
 xij = ai
j 1
for 1  i  m
m
 xij = bj
i 1
xij  0
for 1 j  n
for 1  i  m and 1  j  n
13
 For the case of Pear Disk Drive Company,
 m = 3 and n = 4
 Total cost of shipments:
250x11 + 420x12 + 380x13 + …… + 1730x34
 Constraints:
x11 + x12 + x13 + x14
= 45
x21 + x22 + x23 + x24
= 120
x31 + x32 + x33 + x34
= 95
x11 + x21 + x31
= 80
x12 + x22 + x32
= 78
x13+ x23 + x33
= 47
x14 + x24 + x34
= 55
 Nonnegativity constraints :
xij  0 for 1  i  3 and 1  j  4
14
 Problem entered in Excel Solver.
 Solution:
 Note: 1. For Cell O9: =SUMPRODUCT (B9:M9,B5:M5).
Copied to O10 to O15
2. For Cell O7 = SUMPRODUCT (B5:M5,B7:M7).
 Total cost is RM297,800
15
 Solver Parameter
16
Infeasible Routes
 Routes Dublin
Chicago & Bangkok
Sioux Falls
were eliminated.
 Total cost is RM298,400.
17
Unbalanced Problems
 Total amount shipped from the sources is not equal to
the total amount required at the sinks.
 Reason: Demand exceeds the supply and vice versa.
 Solution:
Method 1 : Add either a dummy row or a dummy column
to absorb the excess supply or demand
Method 2: Alter the appropriate set of constraints to either
 or  form.
18
Example
Warehouse
Amarillo
Teaneck
Chicago
Sioux Falls
Total Shipment Quantity
(1000s)
90
78
55
55
 Total demand is 278 while total supply is 260.
 To balance problem, add an additional fictitious factory
for the 18-unit shortfall.
 Greedy Heuristic: Add dummy row (4 rows and 4 colums)
(All shortfall to Sioux Falls warehouse )
p/s: One can assign zero to all costs in the dummy column.
19
 Linear Programming:
 The optimal solution calls for assigning the shortfall:
8 units to Chicago and 10 units to Sioux Falls.
20
More General Network
Formulations
 Solving more complex network distribution problems.
 Ex: Transshipment problem.
 A transshipment node is either a supply or a demand
node.
 Balance of flow rules:
If
Apply the Following rule at each Node:
1. Total suppy > total demand
Inflow – outflow  supply or demand
2. Total supply < total demand Inflow – outflow 
Total supply = total demand
supply or demand
Inflow – outflow = supply or demand
21
 Supply = negative number attached to the node
 Demand = Positive number attached to the node
Ex: Pear Disk Drive Problem with taransshipment nodes
22
 There are a total of 10 decision variables.
 The objective function is to minimize
250 x16 + 76 x14 + 380 x15 + 1440 x25 + 1660 x35 +
110 x46 + 95 x48 + 180 x56 + 120 x57 + 195 x58
 Total supply available = 260 units
 Demand = 285 units
 Thus, apply rule 2..
23
 By applying rule 2, eight constraints for this problem:
Node 1 :
Node 2 :
Node 3 :
Node 4 :
Node 5 :
Node 6 :
Node 7 :
Node 8 :
- x14 - x15 - x16  -45
- x25  -120
- x35  -95
x14 – x46 – x48  25
x16 + x46 + x56 –x56 –x57 –x58
x16 + x46 + x56  80
x56  78
x48 + x58  55

47
24
25
26
Design in terms of Manufacturing.
-Also known as DFM (Design for
Manufacturing/Manufacturability)
-general engineering art of designing products in such a
way that they are easy to manufacture.
-This design practice not only focuses on the design aspect
of a part but also on the producibility.
-In simple language it means relative ease to manufacture a
product, part or assembly.
-the important part that need to be reconsider before make
a product. (design, product processing)
27
Design for Logistic
1.
Economic packaging and transportation

Designing products that can be efficiently packed and
stored
2. Concurrent and parallel processing
 Modify the manufacturing process (product design)
3. Postponement/delay differentiation
 Aggregate demand information is more accurate than
disaggregate data.
28
Advantages
 More compact
 Better freight rate (transportation)
 Allows better management of warehouse space
 Reduce lead time (processing)
29
Case Study 1(Transportation)
IKEA – Home furnishing products
Problem Description : To create and maintain flexible
transport solutions in order to meet all the service needs
of customers in the most efficient and environmentally
aware way.
Solution : Uses railway and combined road-rail
transport
30
.
31
Case Study 2 (Parallel Processing)
-Parallel processing is the ability to carry out multiple
operations or tasks simultaneously.
-The concept of parallel manufacturing has been applied
in many industries including the high tech and the
automobile industries.
32
Parallel Processing
Example :
33
Case Study 3 (Postponement)
- Deliberate action to delay final manufacturing or
distribution of a product until receipt of a customer order.
- The concept of postponement was first suggested by
Alderson in 1950. He recommended that producers should
add options or make differentiating changes to the product
close to the time of purchase by the end use customer.
-Benetton, instead of dyeing the yarn first like other sweater
makers, knit plain wool into sweaters and postpone colouring
the entire inventory.
34
Postponement
35
Postponement
The advantage of postponement is based on two
fundamental understandings:
-Aggregate demand of similar products (or same product
group) is more predictable compared to demand for
individual types
- and that it is the finished product which has the short life
cycle and high risk of obsolescence.
36
7.7
Global Supply Chain
An integrated process where several business
entities such as suppliers, manufacturers,
distributors, and retailers work together to plan,
coordinate and control materials, parts and
finished goods from suppliers to customers. One
or more of these business entities operate in
different countries.
37
Objective function of GSCM
 GSGM minimizes a weigted of total cost and activity
days
38
Advantage of Global Supply
Chain
Reduced total costs.
Inventory reduction
Improved fulfillment cycle time
Reduce cycle time
Increased forecast accuracy
Productivity increase
Improved capacity
Expend international connections
Increase intellectual assets
Delivery improvement
39
OBSTACLES:
Potential
Global
Supply
Chain
obstacles
• Inefficient
transportation and
distribution systems
• Market instability
• Language barriers
• Customs
• Political turmoil
• Trade imbalances
• Export surges and
recessions
40
Combating obstacles
•
•
•
•
•
•
•
Join nation groups
Be innovative
Be flexible
Research
New technology
Vertically integrate
Form consortiums
41
Classical Logistic
Issues
Facility Locations
Sourcing
Distribution
42
Cost
• Local labor
rates
• Local space
cost
• International
freight tariffs
• Currency
exchange rates
43
Customs Duty
• Duty rates differ by commodity and
level of assembly
• Duty drawback
• Impact of GATT: Changes over time
• Transfer pricing
• Duty Suspension
44
Taxes on
Corporate
Income
• Different
markups
by country
• Tax havens
and not
havens
• Make vs.
buy effect
45
Offset Trade and Local Content
• Local content requirement for
government purchases
• Content for preferential duty rates
• Offset trade requirements
46
Export
Regulations
• Export licenses
• Denied parties
list
47
Time
•
•
•
•
Lead time
Cycle time
Transit time
Export license
approval cycle
• Customs clearance
48
SELECTING A GLOBAL
SUPPLY CHAIN MODEL :
Different Type of Global
Supply Chain Supply
Models
Own and
manage your
own
infrastructure
Use strategic
alliances
Partner with
an assetbased thirdparty
Partnership
with a global
integrator of
logistics
services
49
Pro
Maximum
Control
Con
Heavy costs
Own and manage
your own
infrastructure
50
Use strategic alliances
Pro
Convenience
Large areas
covered
Con
Unreliable
alliancesprone
51
Partner with an asset- based
third-party
Pro
Operational
standards
Uniform
identity and
marketing
strength
Con
Dedicated
management
structure
Ignorance of
complex
customs
regulation
Lack of
connections
Local
economic
downturns
52
Partnership with a global
integrator of logistics services
Pro
Customer
friendly
In-country
knowledge
True
information
systems
integration
Con
Uniform
standards
Limited use
Less control
53
By implemented a global supply
chain model:
•
•
•
•
•
•
•
•
•
•
Reduced plants from 33 to 12
Manufacturing costs decreased by $500 million
Logistics cost decreased by more than $300 million
Reduce service facilities from 34 to 17
Annual cost reductions of more than $80 million
Physical assets reduced by $34 million
Inventory reduced by $74 million
Increased unit reduction by 500 percent
Increase revenue
Five time more computers were manufactured
54
Summary of Global
Supply Chains
55
56