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Trend in Supply Chain Optimization and Humanitarian Logistics Tokyo University of Tokyo University of Marine Science and Technology Marine Science and.

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Presentation on theme: "Trend in Supply Chain Optimization and Humanitarian Logistics Tokyo University of Tokyo University of Marine Science and Technology Marine Science and."— Presentation transcript:

1 Trend in Supply Chain Optimization and Humanitarian Logistics Tokyo University of Tokyo University of Marine Science and Technology Marine Science and Technology KUBO Mikio KUBO Mikio

2 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

3 What ’ s the Supply Chain? IT(Information Technology) + Logistics = Supply Chain

4 Real System, Transactional IT, Analytic IT Real System=Truck, Ship, Plant, Product, Machine, … Transactional IT POS, ERP, MRP, DRP… Automatic Information Flow Analytic IT Model + Algorithm= Decision Support System brain muscle nerve

5 Levels of Decision Making Strategic Level Tactical Level Operational Level A year to several years; long-term decision making A week to several months; mid-term decision making Real time to several days; short-term decision making Transactional IT Analytic IT

6 Models in Analytic IT Logistics Network Design Inventory Safety stock allocation Inventory policy optimization Production Lot-sizing Scheduling Transportation Delivery Vehicle Routing Multi-period Logistics Network Design Strategic Tactical Operational PlantDC SupplierRetailer

7 Models in Analytic IT Logistics Network Design Inventory Safety stock allocation Inventory policy optimization Production Lot-sizing Scheduling Transportation Delivery Vehicle Routing Multi-period Logistics Network Design Strategic Tactical Operational PlantDC SupplierRetailer

8 Models in Analytic IT Logistics Network Design Inventory Safety stock allocation Inventory policy optimization Production Lot-sizing Scheduling Transportation Delivery Vehicle Routing Multi-period Logistics Network Design Strategic Tactical Operational PlantDC SupplierRetailer

9 Inventory=Blood of Supply Chain Time Inventory acts as glue connecting optimization systems PlantDC SupplierRetailer Raw material Work-in-processFinished goods

10 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 (stock- out) cost

11 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)

12 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 Period Resource Upper Bound

13 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

14 Lot-size Inventory Cycle inventory when the speed of demand is not constant Trade-off: fixed cost ->Lot-sizing, multi-period LND Time Inventory Level

15 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

16 Classification of Inventory Time Safety Inventory Cycle Inventory Lot-size Inventory In-transit (Pipeline) Inventory It ’ s hard to separate them but … They should be determined separately to optimize the trade-offs Seasonal Inventory

17 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?

18 Trade-off in LND Model: N umber of Warehouses v.s. Number of warehouses Service lead time ↓ Inventory cost ↑ Overhead cost ↑ Outbound transportation cost ↓ Inbound transportation cost ↑

19 Trade-off: In-transit inventory cost v.s. Transportation cost In-transit inventory costTransportation cost

20 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)

21 Trade-off: Overtime v.s. Seasonal Inventory Cost Demand Period Resource Upper Bound Constant Production Inventories Variable Production Overtime Overtime penaltySeasonal inventory

22 Mixed Integer Programming (MIP) + Concave Cost Minimization Safety Inv. Cost BOM or Recipe

23 Safety Stock Allocation Decision support in tactical level Determine the allocation of safety stocks in the SC for given service levels Safety InventoryService Level +Risk Pooling (Statistical Economy of Scale)

24 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.

25 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

26 The Relation between Lead-time and (Average, Safety, Maximum) Inventory

27 Guaranteed Lead-time Guaranteed lead-time (LT) : Each facility guarantees to deliver the item to his customer within the guaranteed lead-time Facility i 1 Production time T i = 3 2 Guaranteed LT of upstream facility =1 day = Entering LT LI i Guaranteed LT to downstream facility L i =2 days 2 Safety inv. =2 days

28 Net Replenishment Time Net replenishment time (NRT) : = LT i +T i -L i Facility i 1 Production time T i = 3 2 Guaranteed LT of upstream facility =1 day = Entering LT LI i 2 Safety inv. =2 days Guaranteed LT to downstream facility L i =2 days

29 Safety Stock Allocation Formulation net replenishment time maximum demand upper bound of guaranteed LT

30 Algorithms for Safety Stock Allocation Concave cost minimization using piece- wise linear approximation Dynamic programming (DP) for tree networks Metaheuristics Local Search (LS), Iterated LS, Tabu Search

31 A Real Example: Ref. Managing the Supply Chain – The Definitive Guide for the Business Professional – by Simchi-Levi, Kaminski,Simchi-Levi Part7 Denver ($2.5) Part 6 Raleigh ($3) Final Demand N(100,10) Guaranteed LT =30 days 5 Part 5 Charleston ($12) Part 4 Malaysia ($180) Part 3 Montgomery ($220) Part 2 Dallas ($0.5) Part 1 Dallas ($260) x2 43,508$ (40%Down) What if analysis: Guaranteed LT=15 days ->51,136$

32 Inventory Policy Optimization Decision support in operational/tactical level Determine various parameters for inventory control policies Classical Newsboy Model Classical Economic Ordering Quantity Model Safety Inventory Lost Sales Cycle Inventory Fixed Ordering

33 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

34 (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

35 (Q,R) Policy and (s,S) Policy R (=s) R+Q (=S) Lead time (Q,R) (s,S) Inventory position Time In-hand inventory

36 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 Mon.Tue.Wed.Thu. Demand Arrival of the order of Mon. ( Lead time L =1 day ) Order L=1

37 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

38 Lot-size Optimization Decision support in tactical level Optimize the trade-off between set-up cost and lot-size inventory Lot-size Inv. Setup Cost

39 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

40 Scheduling Optimization Decision support in operational level Optimization of the allocation of activities (jobs, tasks) over time under finite resources (such as machines) Machine 1 Machine 2 Machine Time

41 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. Machine 1 Machine 2 Machine Time

42 Solution Methods for Scheduling Myopic heuristics Active schedule generation scheme Non-delay schedule generation scheme Dispatching rules Constraint programming Metaheuristics

43 Vehicle Routing Optimization Depot Customers Routes service time waiting time earliest time Customer latest time service time

44 Algorithms for Vehicle Routing Saving (Clarke-Wright) method Sweep (Gillet-Miller) method Insertion method Local Search Metaheuristics

45 History of Algorithms for Vehicle Routing Problem Construction Method (Saving, Insertion) Local Search GeneralizedAssignment Location Based Heuristics Tabu Search GRASP (Greedy Randomized Adaptive Search Procedure) AMP (Adaptive Memory Programming) Programming) Approximate Algorithm Exact Algorithm K-Tree Relax. State Space Relax. Set Partitioning Approach Hierarchical Building Block Method Cutting Plane Route Selection Heuristics Simulated Annealing Genetic Algorithm 2000 SweepMethod

46 Disruption Supply Chain “ Risk ” Management Proactive and response approaches to cope with supply chain disruptions. Time Performance ProactiveResponse Recovery

47 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.

48 Related Area Risk Management Business Continuity Planning (BCP)/ Business Continuity Management (BCM) But, both did not work well … Humanitarian Logistics / Humanitarian Supply Chain

49 … 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)

50 Risk Mapping Regular risk : demand/supply uncertainty Irregular risk : disruption / disaster Impact Frequency Typhoon Earthquake Strike Exchange Rate Line Stop Supply Delay Defective Product

51 Risk Classification (1) Supply Risk Plant Production Line Transportation Resource Warehouse Demand Risk Internal Risk Environmental Risk

52 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,...

53 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, …

54 Strengthen Strategies Proactive Robustness Resiliency Redundancy Flexibility Compatibility Disruption Time Performance ProactiveResponse – Agility – Visibility Robustness Time Resiliency Performance Resiliency

55 Redundancy -Strategic Inventory- Inventory 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.

56 Flexibility of Sourcing -Multiple Sourcing Strategy- Plant Supplier Single sourcing Dual sourcing Make-and-buy Plant Supplier A Supplier B (Contract) Supplier Plant or

57 Flexible Production Strategy 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. 1-flexibility2-flexibilityFull-flexibility

58 Flexible Transportation Strategy Multi-mode Multi-carrier Multi-route

59 Compatibility Risk Pooling Delayed Differentiation / Postponement

60 Coping Strategies / Risk Mapping Impact Frequency Typhoon Earthquake Strike Exchange Rate Line Stop Supply Delay Defective Product Avoid Transfer Redundancy Flexibility Robustness by KAIZEN/ TQC Visibility Alignment Robustness by PM Reduce Impact Reduce Probability

61 Supply Chain “ Risk ” Optimization What If Analysis Stochastic Programming (Scenario Approach) Disruption Time Performance ProactiveResponse Logistics Network Design Safety Stock Allocation (Strategic, Tactical) Scheduling Vehicle Routing Transportation (Operational) Here & Now Variables Recourse Variables

62 Optimization Models for SCRM Logistics Network Design Inventory Safety stock allocation Inventory policy optimization Production Lot-sizing Scheduling Transportation Delivery Vehicle Routing Multi-period Logistics Network Design Strategic Tactical Operational Stochastic /Robust Extensions Dynamic Pricing Sourcing Decision Quick Solution without IT


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