Facility Location Inventory Management Dr Ron TibbenLembke Location
Facility Location Inventory Management Dr. Ron Tibben-Lembke
Location Decisions Long-term decisions n Difficult to reverse n Affect fixed & variable costs n ¨ Transportation costs (25% of price) ¨ Other costs: taxes, wages, rent n Objective: maximize benefit of location to firm
What factors should we consider? Skilled workforce n Environmental laws / cost of compliance n Cost of utilities, labor, taxes n Suppliers close by – fast & cheap access n Customers close by n Competitors close by? Skilled labor pool n International - control issues? n
Service Facilities – Traffic focus n Revenue changes a huge amount, depending on the location. ¨ Old Navy in Stead because of cheap land? ¨ Location, location: you need traffic ¨ Make it convenient! ¨ vitamins: need enough, but it has to be the right kind ¨ people who would want to buy your products when they are there. n Cost probably doesn’t change nearly as much, by location ¨ All malls have high rent
Wal-Mart Office Max Win. Co Toys Party
“I-80 & Mc. Carran” sounds great. Kmart Sins: Can’t see from anywhere - see where we’re going Very circuitous entry - feels inconvenient, no matter how long it actually takes
Cost Focus n Revenue does not vary much, depending on the location. ¨ Customers don’t care if your warehouse is in Sparks or Sacramento n Location is a major cost driver ¨ Impacts shipping, labor, production costs ¨ Varies greatly by location
Cost Minimization Identify the costs that will vary most with the location you choose. ¨ Transportation, taxes, labor, ¨ Facility construction cost, utilities Other considerations ¨ Proximity of services, suppliers ¨ Quality of life ¨ Government incentives
Cost Focus Process Overview 1. Identify general region to locate in n 2. Identify a list of candidate cities n n 3. Usually based on mostly on transp. costs Choose cities with good transp. Access Estimate labor cost & availability, facilities costs Select metro area, identify candidate properties. n Find cost of building or leasing individual properties
Case Study: Importing from China to E. Coast
Customer Location
More detail on East Coast possibilities
Interstate Detail
China to U. S. Container Rates NY / NJ $3, 600 36 days Wilmington DE $3, 950 36 days (door) Norfolk $3, 600 34 days Charleston $3, 600 35 days New Orleans $3, 200 36 days Atlanta $3, 200 37 days (door)
Drayage Rates North Allentown 575 428 Harrisburg 750 265 656 Baltimore 350 Philadelphia 305 850 Elizabeth, NJ 850 295 343 305 375 Wilmington 825 305 375 750 780 950 1125 888 Roanoke 750 Norfolk 725 950
China to Long Beach
Landbridge Data Columbus $3000, 21 days Cincinnati $2925, 21 d Louisville $3050, 20 d Murray $3350, 22 d Memphis $2900, 18. 5 d Nashville $3300, 22 d Atlanta $3300, 23 d
Interstate Access
Distribution Center Location Minimize demand-weighted distance: distance to each customer times the volume of shipments to the customer n How many to build? n Where to build? n
Case Study: Retailer Location of a 5 th returns processing facility n Addresses of 2125 Continental U. S. stores n Location of 4 Return Goods Processing Centers n List of all return shipments from each store, including pounds and # pallets n Calculated actual highway distances from every store to its DC n
Local Streets
Transportation Cost Approx. Current Pallets: 205, 254 n Current Pallet Miles: 77. 9 m n Cost / pallet-mile 11. 68 cents n Pallet-Mile = 1 pallet traveling 1 mile n Minimize average distance traveled n
Solution Software n n Some locations must have a facility Considers adding a facility at every existing store ¨ We n n won’t really build next to a store, but that’s ok Finds one best facility to add Finds second best facility to add Reconsider first added facility, then second, etc. Improvement heuristics, optimal methods
Current RCs
Dallas Realignment
Close 1 existing RDC
Location Methods n Minimize demand-weighted distance ¨ Center of Gravity – minimizing demand-weighted distances of one facility ¨ Ardalan – minimize transportation of multiple facilities, but must locate by customers ¨ (P-Median Problem, Maximum Covering) n n Factor Weighting – consider qualitative factors Break-even – Consider fixed & variable costs
Center of Gravity n n n Compute X and Y coordinates separately dix is the X coordinate of location i. diy is the Y coordinate of i. Wi is the X demand at i. CX and CY are the coordinates of the DC.
Center of Gravity Example 1 You need to decide where to build a new DC for Motorola. n It needs to serve wholesalers in Reno, Dallas, and Chicago. n Locate these cities on an unscientific, rectangular grid. n Grid must maintain relative distances, but X and Y grids could be different. n
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Center of Gravity Method City Demand n Reno is at 17, 55 100 n Fort Worth is at 78, 20 90 n Chicago is at 110, 65. 120 n Demand is TL/month
Center of Gravity
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North Platte Sharon Springs Salina KS
Compromise Solution n Closest town is Sharon Springs, KN ¨ Population 872 ¨ 30 miles from I-70. ¨ Probably not a good choice Salina, KN puts us at I-70 and I-35 n North Platte NE is at I-80 and 83. n ¨ Access to Dallas less convenient
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Finalizing City n Go where other warehouses are ¨ More choice in pre-built buildings ¨ Cheaper, easier to build a new one ¨ More trucks to and from town, means more carriers there, means cheaper rates. ¨ Backhaul situation n Get estimates of inbound, outbound trucking costs. ¨ Provide lists of # loads per year to each destination, from each source
Center of Gravity Example 2 You need to decide where to locate a DC in South Dakota X Y Demand n Pierre 78 47 50 n Watertown 150 65 8 n Sioux Falls 160 25 90 n Rapid 12 42 60 n
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Center of Gravity
100 80 60 40 20 0 0 20 40 60 80 100 120 140 160
Ardalan Heuristic n n n Need a matrix of distances or costs from each customer location to every other location Demand at each location Weight – give higher weight to more important customers – their pain of traveling a longer distance is worth more. Only consider locating where customers are Identify the one best place to locate at, then the second one to add, then the third, etc.
Ardalan Heuristic Minimize weighted distance traveled To From A B C D Dem. Weight A 0 11 8 12 10 1. 1 B 11 0 10 7 8 1. 4 C 8 10 0 9 20 0. 7 D 9. 5 7 9 0 12 1. 0 n
Ardalan Method Expected demand at each location. n Weight represents importance of serving location (bigger = more important) n Step 1: Multiply distances * weights * demand n A to B: 11 * 10 = 121 n
Ardalan Method Step 2. Add up values in columns From A B C D A 0 121 88 132 B 123. 2 0 112 78. 4 C 112 140 0 126 D 114 84 108 0 349. 2 345 308 336. 4
Ardalan Method Choose smallest value as first site. From A B C D A 0 121 88 132 B 123. 2 0 112 78. 4 C 112 140 0 126 D 114 84 108 0 349. 2 345 308 336. 4
Ardalan Method 3. If larger, set each cost equal to cost in same row in the chosen column From A B C D A 0 112 0 108 B 88 0 0 84 C 88 112 0 108 D 88 78. 4 0 0 220 172 308 166. 4
Ardalan Method Get rid of previously chosen column. Sum, choose smallest sum. From A B D A 0 88 88 B 112 0 78. 4 C 0 0 0 D 108 84 0 220 172 166. 4
Ardalan Method Repeat 3 & 4 until enough sites chosen. From A B D A 0 88 88 B 78. 4 0 78. 4 C 0 0 0 D 0 0 0 78. 4 88 166. 4
Ardalan Method Repeat 3 & 4 until enough sites chosen. From A B A 0 88 B 78. 4 0 C 0 0 D 0 0 78. 4 88
Ardalan Summary What we decided is that if we only want to build one location, it should be in C. n If we want to build two, they should be in C and D. If we add a third one, it should be in A. n
Ardalan Summary n n Assumes that we have to locate in the same city as one of our customers, which is not always the case. However, it can be used to find more than one location. Center of Gravity does not try to locate in the same city as one of the customers, but can only set one site. If we choose the same sites as customers A and X, we obviously don’t really have to put the warehouses in those exact cities.
P-Median Problem Minimize average weighted distance to customers, when locating P facilities, where P>=1. n Can consider 100 s of locations. n Complex to solve – there is software for this. n
Maximum Covering Problem A facility can “cover” a customer if the customer is within X miles of the facility. n Try to find the best location, and minimum number of facilities to cover all demands. n Cover a table with plates. n Math also very hard. n
Comparison of Results Demand Covered (Using Distances of 150, 200, 250) Number of Facilities
Solving large problems
Incremental or clean-slate apprach Take into account existing facilities n What is the best location to add, given the existing facilities? n What is the best to add, if we were to close down one of the current facilities? n Unfortunately, only P-Median or Maximum Covering can deal with these. n
Factor Rating Method n n n n Most widely used method? Useful for service or industrial facilities: can include intangible, qualitative factors List relevant factors, assign a weight Develop a scale for each factor Score each factor using the scale Multiply scores by weights, add up Choose location with highest total score Kind of like “Miss America”
Factor Rating Example n n We need to decide where to build a new coffee roasting plant. There are two possible locations: Dallas, and Denver. We consider the following factors ¨ Transp: annual trucking costs in $k ¨ Lease: annual costs in $k ¨ Labor availability: scale 1 -10, unemployment, related industries ¨ Quality of life: scale 1 -10: outdoor activities, cultural, sports, education
Factor Rating Example Using a scoring system we developed, we have the following. Factor Weight TX CO Transportation 0. 5 900 1, 023 Plant Lease Cost 0. 3 45 39 Labor availability 0. 2 10 8 Quality of Life 0. 1 7 9. 5 n
Normalizing Scores All factors must be scored on the same scale, like 1 -10, or 0 -1. 0, etc. n Costs need to be re-scaled n ¨ Lowest cost site gets a 10. ¨ More expensive site gets 39/45 * 10 or 900/1, 023 * 10
Factor Rating Example TX Factor Wt Tr 0. 4 10 Plant 0. 3 Labor 0. 2 Q Life 0. 1 TOTAL TX is best CO Raw Wtd 4. 00 8. 80 8. 7 2. 61 10 2. 00 7 0. 70 9. 31 Raw Wtd 3. 52 10 3. 00 8 1. 60 9. 5 0. 95 9. 07
Possible Approach Use Ardalan to find out which general regions to locate in (state / county). n Use factor weighting to choose city. n Ardalan has disadvantage of choosing weights -- difficult to set levels. n
Break-Even Analysis n n n Determine fixed and variable costs for each location Fixed cost: how much it would cost to open a facility there Variable cost: how much total costs would increase as production increases: ¨ Transportation costs ¨ Labor costs ¨ Taxes ¨ Increased construction costs
Locating Service Facilities Using Linear Regression n Collect data about your current facilities n Use regression to determine which variables have a significant impact on profits n Choose new facilities which have these characteristics
Method Comparison Center of gravity minimizes average distance for one facility only. n Ardalan Minimizes weighted distances for more than one facility. n Breakeven: fixed & variable costs. n Factor weighting considers many other important aspects of location, but does not minimize distance. n
Transportation Method You have 3 DCs, and need to deliver product to 4 customers. D 2 A 10 E 4 B 10 C 10 F 12 G 11 Find cheapest way to satisfy all demand
Solving Transportation Problems n n n Trial and Error Linear Programming – ooh, what’s that? ! Tell me more! D E F G A 10 9 8 7 B 10 11 4 5 C 8 7 4 8
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