2 Outline What is it? Methodology Solution Techniques. Modeling Data AggregationValidationSolution Techniques.
3 The Logistics Network The Logistics Network consists of: Facilities: Vendors, Manufacturing Centers, Warehouse/ Distribution Centers, and CustomersRaw materials and finished products that flow between the facilities.
5 Logistics Design Decisions Determine the appropriate number of warehousesDetermine the location of each warehouseDetermine the size of each warehouseAllocate space for products in each warehouseDetermine which products customers will receive from each warehouse
6 Decision Classifications Strategic Planning: Decisions that typically involve major capital investments and have a long term effect1. Determination of the number, location and size of new plants, distribution centers and warehouses2. Acquisition of new production equipment and the design of working centers within each plant3. Design of transportation facilities, communications equipment, data processing means, etc.
7 Decision Classifications Tactical Planning: Effective allocation of manufacturing and distribution resources over a period of several months1. Work-force size2. Inventory policies3. Definition of the distribution channels4. Selection of transportation and trans-shipment alternatives
8 Decision Classifications Operational Control: Includes day-to-day operational decisions1. The assignment of customer orders to individual machines2. Dispatching, expediting and processing orders3. Vehicle scheduling
9 Network Design: Key Issues Pick the optimal number, location, and size of warehouses and/or plantsDetermine optimal sourcing strategyWhich plant/vendor should produce which productDetermine best distribution channelsWhich warehouses should service which customers
10 Objective of Logistics Management Design or configure the logistics network so as to minimize annual system-wide cost subject to a variety of service level requirements
11 Network Design: Key Issues The objective is to balance service level againstProduction/ purchasing costsInventory carrying costsFacility costs (handling and fixed costs)Transportation costsThat is, we would like to find a minimal-annual-cost configuration of the distribution network that satisfies product demands at specified customer service levels.
12 Network Design Tools: Major Components MappingMapping allows you to visualize your supply chain and solutionsMapping the solutions allows you to better understand different scenariosColor coding, sizing, and utilization indicators allow for further analysisDataData specifies the costs of your supply chainThe baseline cost data should match your accounting dataThe output data allows you to quantify changes to the supply chainEngineOptimization Techniques
13 Mapping Allows You to Visualize Your Supply Chain
14 Displaying the Solutions Allows you To Compare Scenarios
15 Data for Network Design 1. A listing of all products2. Location of customers, stocking points and sources3. Demand for each product by customer location4. Transportation rates5. Warehousing costs6. Shipment sizes by product7. Order patterns by frequency, size, season, content8. Order processing costs9. Customer service goals
16 Too Much Information Customers and Geocoding Sales data is typically collected on a by-customer basisNetwork planning is facilitated if sales data is in a geographic database rather than accounting database1. Distances2. Transportation costsNew technology exists for Geocoding the data based on Geographic Information System (GIS)
17 Aggregating Customers Customers located in close proximity are aggregated using a grid network or clustering techniques. All customers within a single cell or a single cluster are replaced by a single customer located at the centroid of the cell or cluster. We refer to a cell or a cluster as a customer zone.
18 Impact of Aggregating Customers The customer zone balances1. Loss of accuracy due to over aggregation2. Needless complexityWhat affects the efficiency of the aggregation?1. The number of aggregated points, that is the number of different zones2. The distribution of customers in each zone.
19 Why Aggregate? The cost of obtaining and processing data The form in which data is availableThe size of the resulting location modelThe accuracy of forecast demand
20 Recommended Approach Use at least 300 aggregated points Make sure each zone has an equal amount of total demandPlace the aggregated point at the center of the zone
21 Testing Customer Aggregation 1 Plant; 1 ProductConsidering transportation costs onlyCustomer dataOriginal Data had 18,000 5-digit zip code ship-to locationsAggregated Data had digit ship-to locationsTotal demand was the same in both cases
22 Comparing Output Cost Difference < 0.05% Total Cost:$5,796,000 Total Customers: 18,000Total Cost:$5,793,000Total Customers: 800Cost Difference < 0.05%
23 Product GroupingCompanies may have hundreds to thousands of individual items in their production line1. Variations in product models and style2. Same products are packaged in many sizesCollecting all data and analyzing it is impractical for so many product groups
24 A Strategy for Product Aggregation Place all SKU’s into a source-groupA source group is a group of SKU’s all sourced from the same place(s)Within each of the source-groups, aggregate the SKU’s by similar logistics characteristicsWeightVolumeHolding Cost
25 Within Each Source Group, Aggregate Products by Similar Characteristics Rectangles illustrate how to cluster SKU’s.
26 Test Case for Product Aggregation 5 Plants25 Potential Warehouse LocationsDistance-based Service ConstraintsInventory Holding CostsFixed Warehouse CostsProduct Aggregation46 Original products4 Aggregated productsAggregated products were created using weighted averages
28 Minimize the cost of your logistics network without compromising service levels OptimalNumberof Warehouses
29 The Impact of Increasing the Number of Warehouses Improve service level due to reduction of average service time to customersIncrease inventory costs due to a larger safety stockIncrease overhead and set-up costsReduce transportation costs in a certain rangeReduce outbound transportation costsIncrease inbound transportation costs
30 Industry Benchmarks: Number of Distribution Centers PharmaceuticalsFood CompaniesChemicalsAvg.# ofWH31425- High margin product- Service not important (oreasy to ship express)- Inventory expensiverelative to transportation- Low margin product- Service very important- Outbound transportationexpensive relative to inboundSources: CLM 1999, Herbert W. Davis & Co; LogicTools
31 A Typical Network Design Model Several products are produced at several plants.Each plant has a known production capacity.There is a known demand for each product at each customer zone.The demand is satisfied by shipping the products via regional distribution centers.There may be an upper bound on total throughput at each distribution center.
32 A Typical Location Model There may be an upper bound on the distance between a distribution center and a market area served by itA set of potential location sites for the new facilities was identifiedCosts:Set-up costsTransportation cost is proportional to the distanceStorage and handling costsProduction/supply costs
33 Complexity of Network Design Problems Location problems are, in general, very difficult problems.The complexity increases withthe number of customers,the number of products,the number of potential locations for warehouses, andthe number of warehouses located.
34 Solution Techniques Mathematical optimization techniques: 1. Heuristics: find “good” solutions, not necessarily optimal2. Exact algorithms: find optimal solutionsSimulation models: provide a mechanism to evaluate specified design alternatives created by the designer.
35 Heuristics and the Need for Exact Algorithms Single productTwo plants p1 and p2Plant P1 has an annual capacity of 200,000 units.Plant p2 has an annual capacity of 60,000 units.The two plants have the same production costs.There are two warehouses w1 and w2 with identical warehouse handling costs.There are three markets areas c1,c2 and c3 with demands of 50,000, 100,000 and 50,000, respectively.
37 Why Optimization Matters? $0D = 50,000$3Cap = 200,000$4$5$5D = 100,000$2$4$1$2Cap = 60,000$2D = 50,000Production costs are the same, warehousing costs are the same
38 Traditional Approach #1: Assign each market to closet WH Traditional Approach #1: Assign each market to closet WH. Then assign each plant based on cost.D = 50,000Cap = 200,000$5 x 140,000D = 100,000$2 x 50,000$1 x 100,000$2 x 60,000Cap = 60,000$2 x 50,000D = 50,000Total Costs = $1,120,000
39 Traditional Approach #2: Assign each market based on total landed cost $0D = 50,000$3Cap = 200,000P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4$4$5$5D = 100,000$2P1 to WH1 $4P1 to WH2 $6P2 to WH1 $8P2 to WH 2 $3$4$1$2Cap = 60,000$2D = 50,000P1 to WH1 $5P1 to WH2 $7P2 to WH1 $9P2 to WH 2 $4
40 Traditional Approach #2: Assign each market based on total landed cost $0D = 50,000$3Cap = 200,000P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4$4$5$5D = 100,000$2P1 to WH1 $4P1 to WH2 $6P2 to WH1 $8P2 to WH 2 $3$4$1$2Cap = 60,000$2D = 50,000P1 to WH1 $5P1 to WH2 $7P2 to WH1 $9P2 to WH 2 $4Market #1 is served by WH1, Markets 2 and 3are served by WH2
41 Traditional Approach #2: Assign each market based on total landed cost $0 x 50,000D = 50,000$3 x 50,000Cap = 200,000P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4$5 x 90,000D = 100,000P1 to WH1 $4P1 to WH2 $6P2 to WH1 $8P2 to WH 2 $3$1 x 100,000$2 x 60,000Cap = 60,000$2 x 50,000D = 50,000P1 to WH1 $5P1 to WH2 $7P2 to WH1 $9P2 to WH 2 $4Total Cost = $920,000
42 The Optimization Model The problem described earlier can be framed as the following linear programming problem.Letx(p1,w1), x(p1,w2), x(p2,w1) and x(p2,w2) be the flows from the plants to the warehouses.x(w1,c1), x(w1,c2), x(w1,c3) be the flows from the warehouse w1 to customer zones c1, c2 and c3.x(w2,c1), x(w2,c2), x(w2,c3) be the flows from warehouse w2 to customer zones c1, c2 and c3
43 The Optimization Model The problem we want to solve is:min 0x(p1,w1) + 5x(p1,w2) + 4x(p2,w1)+ 2x(p2,w2) + 3x(w1,c1) + 4x(w1,c2)+ 5x(w1,c3) + 2x(w2,c1) + 2x(w2,c3)subject to the following constraints:x(p2,w1) + x(p2,w2) 60000x(p1,w1) + x(p2,w1) = x(w1,c1) + x(w1,c2) + x(w1,c3)x(p1,w2) + x(p2,w2) = x(w2,c1) + x(w2,c2) + x(w2,c3)x(w1,c1) + x(w2,c1) = 50000x(w1,c2) + x(w2,c2) =x(w1,c3) + x(w2,c3) = 50000all flows greater than or equal to zero.