Trend in Supply Chain Optimization
and Humanitarian Logistics
Tokyo University of
Marine Science and Technology
KUBO Mikio
Agenda
Definition of the Supply Chain (SC) and
Logistics
Decision Levels of the SC
Classification of Inventory
Basic Models in the SC




Logistics Network Design
Inventory
Production Planning
Vehicle Routing
SC Risk Management and Humanitarian SC
What’s the Supply Chain?
IT(Information Technology)＋Logistics
＝Supply Chain
Real System, Transactional IT,
Analytic IT
brain
解析的IT
処理的IT
nerve
Analytic IT
Model＋Algorithm=
Decision Support System
Transactional IT
POS, ERP, MRP, DRP…
Automatic Information Flow
Real System=Truck, Ship, Plant, Product, Machine, …
muscle
実システム
Levels of Decision Making
Strategic Level
A year to several years; long-term decision making
Analytic IT
Tactical Level
A week to several months; mid-term decision making
Operational Level
Transactional IT
Real time to several days;
short-term decision making
Models in Analytic IT
Supplier
Plant
Retailer
DC
Logistics Network Design
Strategic
Multi-period Logistics Network Design
Tactical
Operational
Inventory
Production
Safety stock allocation
Inventory policy
optimization
Lot-sizing
Scheduling
Transportation
Delivery
Vehicle Routing
Models in Analytic IT
Supplier
Strategic
Plant
Retailer
DC
Logistics Network Design
Multi-period Logistics Network Design
Tactical
Operational
Inventory
Production
Safety stock allocation
Inventory policy
optimization
Lot-sizing
Scheduling
Transportation
Delivery
Vehicle Routing
Models in Analytic IT
Supplier
Plant
Strategic
Retailer
DC
Logistics Network Design
Multi-period Logistics Network Design
Tactical
Operational
Inventory
Safety stock allocation
Inventory policy
optimization
Production
Lot-sizing
Scheduling
Transportation
Delivery
Vehicle Routing
Inventory=Blood of Supply Chain
Inventory acts as glue connecting optimization systems
Supplier
Raw material
Plant
Work-in-process
DC
Retailer
Finished goods
Time
Classification of Inventory
In-transit (pipeline) inventory
Trade-off: transportation cost or production speed
Seasonal inventory
Trade-off: resource acquisition or overtime cost，setup
cost
Cycle inventory
Trade-off : transportation (or production or ordering)
fixed cost
Lot-size inventory
Trade-off: fixed cost
Safety inventory
Trade-off: customer service level， backorder (stockout) cost
In-transit (pipeline) Inventory
Inventory that are in-transit of products
Trade-off: transportation cost or
transportation/production speed
->optimized in Logistics Network Design (LND)
Seasonal Inventory
Inventory for time-varying (seasonal) demands
Trade-off: resource acquisition or overtime cost
-> optimized in multi-period LND
Trade-off: setup cost
-> optimized in Lot-sizing
Demand
Resource Upper Bound
Period
Cycle Inventory
Inventory caused by periodic activities
Trade-off : transportation fixed cost -> LND
Trade-off: ordering fixed cost
-> Economic Ordering Quantity (EOQ)
Inventory
Level
demand
Cycle Time
Lot-size Inventory
Cycle inventory when the speed of
demand is not constant
Trade-off: fixed cost
->Lot-sizing, multi-period LND
Inventory
Level
Time
Safety Inventory
Inventory for the demand variability
Trade-off: customer service level
->Safety Stock Allocation, LND
Trade-off: backorder (stock-out) cost
->Inventory Policy Optimization
Classification of Inventory
Seasonal Inventory
Cycle Inventory
Lot-size Inventory
Safety Inventory
In-transit (Pipeline) Inventory
Time
It’s hard to separate them but…
They should be determined separately to optimize the trade-offs
Logistics Network Design
Decision support in strategic level
Total optimization of overall supply chains
Example
 Where should we replenish pars?
 In which plant or on which production line
should we produce products?
 Where and by which transportation-mode
should we transport products?
 Where should we construct (or close) plants
or new distribution centers?
Trade-off in LND Model:
Ｎumber of Warehouses v.s.
Number
of warehouses
輸送中在庫費用
•
•
•
•
•
Service lead time ↓
Inventory cost ↑
Overhead cost ↑
Outbound
輸送費用 transportation cost ↓
Inbound transportation cost ↑
Trade-off:
In-transit inventory cost v.s. Transportation cost
輸送中在庫費用
In-transit
inventory cost
輸送費用
Transportation
cost
Multi-period Logistics Network Design
Decision support in tactical level
An extension of MPS (Master Production System) for
production to the Supply Chain
Treat the seasonal demand explicitly
Demand
Period (Month)
Trade-off:
Overtime v.s. Seasonal Inventory Cost
資源超過ペナルティ
作り置き在庫費用
Overtime
penalty Seasonal
inventory
（残業費）
Demand
Resource Upper Bound
Period
Constant
Production
Inventories
Overtime
Variable
Production
Mixed Integer Programming (MIP) +
Concave Cost Minimization
BOMororRecipe
Recipie
BOM
×
３
Safety Inv. Cost
Warehouses Customer Gropus
Plant s
Suppliers
Product ion Lines
Safety Stock Allocation
Decision support in tactical level
Determine the allocation of safety
stocks in the SC for given service levels
安全在庫費用
Safety
Inventory
サービスレベル
Service Level
+Risk Pooling
＋統計的規模の経済
（リスク共同管理）
(Statistical Economy of Scale)
Basic Principle of Inventory
Economy of scale in statistics: gathering
inventory together reduces the total
inventory volume.
-> Modern supply chain strategies



risk pooling
delayed differentiation
design for logistics
Where should we allocate safety stocks to minimize the
total safety stock costs so that the customer service level
is satisfied.
Lead-time and Safety Stock
Normal distribution with average demand μ，
standard deviation σ
Service level （the probability of no stocking
out） 95%->safety stock ratio 1.65
Lead-time (the time between order and
arrival） L
Max Inv.Volume＝
  L＋SafetyStock Ratio   L
The Relation between Lead-time and
(Average, Safety, Maximum) Inventory
3000
2500
2000
Average
Max.
Safety
1500
1000
500
0
0
5
10
Lead-time
15
20
Guaranteed Lead-time
Guaranteed lead-time (LT)：Each facility
guarantees to deliver the item to his
customer within the guaranteed leadtime
Guaranteed LT to
Safety inv.
＝２ days
2
Guaranteed LT
of upstream facility
=1 day
= Entering LT
LIi
1
downstream facility
Li ＝２ days
2
Production time
Facility i
Ti ＝3
Net Replenishment Time
Net replenishment time (NRT)：
＝LTi +Ti -Li
Safety inv.
＝２ days
2
Guaranteed LT
of upstream facility
=1 day
= Entering LT
LIi
1
Guaranteed LT to
downstream facility
Li ＝２ days
2
Production time
Facility i
Ti＝3
Safety Stock Allocation
Formulation
maximum demand
net replenishment time
upper bound of guaranteed LT
Algorithms for Safety Stock Allocation
Concave cost minimization using piecewise linear approximation
Dynamic programming (DP) for tree
networks
Metaheuristics
Local Search (LS), Iterated LS, Tabu
Search
A Real Example: Ref.
Managing the Supply Chain –The
Definitive Guide for the Business Professional –by Simchi-Levi,
Kaminski,Simchi-Levi
15 x2
37
5
28
Part 4
Malaysia ($180)
37
3
Part 5
Charleston ($12)
58
4
Part7
Denver ($2.5)
29
58
37
8
Part 6
Raleigh ($3)
Part 2
Dallas ($0.5)
39
37
15
17
Part 3
Montgomery ($220)
Part 1
Dallas ($260)
30
15 15
30
Final Demand
N(100,10)
Guaranteed LT
=30 days
43,508$ (40%Down)
What if analysis:
Guaranteed LT=15 days ->51,136$
Inventory Policy Optimization
Decision support in operational/tactical level
Determine various parameters for inventory
control policies
品切れ費用
Safety
Inventory
安全在庫費用
Lost
Sales
Classical Newsboy Model
発注（生産）固定費用
Cycle Inventory
サイクル在庫費用
Fixed
Ordering
Classical Economic Ordering
Quantity Model
Base stock Policy (Multi Period Model)
Base stock level s* ＝ target of the
inventory position
Inventory (ordering) position=
In-hand inventory+In-transit inventory
(inventory on order) -Backorder
Base stock policy: Monitoring the inventory
position in real time; if it is below the base
stock level, order the amount so that it
recovers the base stock level
(Q,R) and (s,S) Policies
If the fixed ordering cost is positive, the
ordering frequency must be considered
explicitly.
(Q,R) policy：If the inventory position is below
a re-ordering point R, order a fixed quantity Q
(s,S) policy：If the inventory position is below
a re-ordering point s, order the amount so that
it becomes an order-up-to level S
(Q,R) Policy and (s,S) Policy
R+Q
(=S)
Inventory
position
(s,S)
(Q,R)
R
(=s)
In-hand
inventory
Lead time
Time
Periodic Ordering Policy
Check the inventory position periodically;
if it is below the base stock level, order
the amount so that it recovers the base
stock level
Order
Mon.
Tue.
Wed.
L=1
Demand
Thu.
Arrival of the order of Mon.（Lead time L＝１day）
Algorithms for Inv. Policy Opt.
base stock，(Q,R)， and (s,S) policies
->Dynamic Programming Recursion
Periodic ordering policy
-> Infinitesimal Perturbation Analysis
During simulation runs, derivatives of
the cost function are estimated and are
used in non-linear optimization
Lot-size Optimization
Decision support in tactical level
Optimize the trade-off between set-up cost and lot-size
inventory
Lot-size
Inv.
段取り費用
Setup
Cost
在庫費用
Algorithms for Lot-sizing
MIP solver with strong forumulation
(Meta)heuristics
Metaheuristics using MIP solver



Relax and Fix
Capacity scaling
ＭＩＰ based neighborhood local search
Scheduling Optimization
Decision support in operational level
Optimization of the allocation of activities (jobs,
tasks) over time under finite resources (such as
machines)
Time
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Machine 1
Machine 2
Machine 3
What is Scheduling?
Allocation of activities (jobs, tasks) over time


Resource constraints. For example, machines, workers,
raw material, etc. may be scare resources.
Precedence relation. For example., some activities
cannot start unless other activities finish.
Time
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Machine 1
Machine 2
Machine 3
Solution Methods for Scheduling
Myopic heuristics



Active schedule generation scheme
Non-delay schedule generation scheme
Dispatching rules
Constraint programming
Metaheuristics
Vehicle Routing Optimization
Customers
earliest time
latest time
Customer
Depot
waiting
time
service time
Routes
service time
Algorithms for Vehicle Routing
Saving (Clarke-Wright) method
Sweep (Gillet-Miller) method
Insertion method
Local Search
Metaheuristics
History of Algorithms for Vehicle Routing
Problem
Approximate Algorithm
Genetic Algorithm
AMP
Tabu
Search
Local Search
Simulated Annealing
Sweep
Method
Generalized
Assignment
Construction Method
(Saving, Insertion)
(Adaptive Memory
Programming)
Location Based
Heuristics
Route Selection
Heuristics
GRASP
(Greedy Randomized
Adaptive Search Procedure)
Exact Algorithm
Set Partitioning Approach
State Space Relax.
Cutting Plane
K-Tree Relax.
1970
1980
1990
2000
Hierarchical
Building Block
Method
Supply Chain “Risk” Management
Performance
Proactive and response approaches to
cope with supply chain disruptions.
Disruption
Recovery
Proactive
Response
Time
Importance of Supply Chain
“Risk”
Increase of disasters


Natural disasters: earthquake, tsunami, SARS (Severe
Acute Respiratory Syndrome), BSE (Bovine Spongiform
Encephalopathy), hurricanes, cyclones and typhoons,
floods, droughts, volcanic eruption, famine and food
insecurity, etc.
Man-made disasters: terrorist attack, CBRNE (Chemical
Biological, Radiological, Nuclear, Explosive) disaster, war,
strike, riot, etc.
Lean supply chain: increases vulnerability.
Globalization: induces long lead time, outsourcing.
Related Area
Risk Management
Business Continuity Planning (BCP)/
Business Continuity Management (BCM)
But, both did not work well …
Humanitarian Logistics /
Humanitarian Supply Chain
Humanitarian Logistics /
Humanitarian Supply Chain
… is a branch of logistics which specializes in
organizing the delivery and warehousing of
supplies during natural disasters to the affected
area and people.
Decentralized
No SCM unit nor trained staffs
Everything is ad hoc
No performance measure (fairness, speed, …)
No information & communication technology
Many players (government, NGOs)
Risk Mapping
Regular risk : demand/supply uncertainty
Irregular risk : disruption / disaster
Frequency
Line Stop
Supply Delay
Strike
Exchange Rate
Typhoon
Defective Product
Earthquake
Impact
Risk Classification (1)
Plant
Warehouse
Supply Risk
Demand Risk
Production
Line
Transportation
Resource
Internal Risk
Environmental Risk
Risk Classification (2)
Disaster risk: natural and man-made disasters
such as landslides, volcanic eruption, drought,
asteroid impacts
Political risk: contracts, laws, regulations
Social risk: child labor / abuse
Intellectual property risk: patents, trademarks,
copyrights
Financial risk, employment risk, reputation
risk, ...
Strategies to Cope with Risk
Accept: just do nothing!
Avoid: remove the risk factor, if possible
Transfer: insurance, option
Alignment: share risk and profit by
contract
Strengthen: make the SC robust,
resilient, redundant, flexible, …
Strengthen Strategies
Proactive




Performance

Robustness
Resiliency
Redundancy
Flexibility
Compatibility
• Response
– Agility
– Visibility
Disruption
Robustness
Time Resiliency
Proactive
Response
Performance
Resiliency
Time
Redundancy
-Strategic InventoryInventory for supply (or production)
disruptions.
That is shared by many supply chain
partners.
We have to distinguish it with the safety
stock to copy with demand uncertainty.
Flexibility of Sourcing
-Multiple Sourcing StrategySingle sourcing
Plant
Supplier
Supplier A
Dual sourcing
Plant
Supplier B
(Contract)
or
Plant
Make-and-buy
Supplier
Flexible Production Strategy
1-flexibility
2-flexibility
Full-flexibility
Graves-Tomlin: 2-flex. is enough for demand uncertainty, i.e.,
2-flex. has the similar performance with full-flex.
Simulation
: 2-flex. is NOT enough for supply uncertainty.
Flexible Transportation Strategy
Multi-mode
Multi-carrier
Multi-route
Compatibility
Risk Pooling
Delayed Differentiation / Postponement
Coping Strategies / Risk Mapping
Reduce Probability
Frequency
Robustness
by PM
Line Stop
Visibility
Alignment
Supply Delay
Robustness
by KAIZEN/
TQC
Defective
Product
Strike
Avoid
Exchange Rate
Typhoon
Reduce Impact
Transfer
Redundancy
Earthquake
Impact
Flexibility
Supply Chain “Risk” Optimization
What If Analysis
Stochastic Programming (Scenario Approach)
Performance
Here & Now
Variables
Recourse Variables
Disruption
Logistics Network Design
Safety Stock Allocation
(Strategic, Tactical)
Proactive
Scheduling
Vehicle Routing
Transportation
(Operational)
Response
Time
Optimization Models for SCRM
Stochastic /Robust
Extensions
Dynamic Pricing
Logistics Network Design
Strategic
Sourcing
Decision
Tactical
Operational
Multi-period Logistics Network Design
Inventory
Production
Safety stock allocation
Inventory policy
optimization
Lot-sizing
Scheduling
Quick Solution
without IT
Transportation
Delivery
Vehicle Routing