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Facility Location Operations Management Dr. Ron Tibben-Lembke
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Location Decisions Long-term decisions Difficult to reverse Affect fixed & variable costs Transportation costs (25% of price) Other costs: taxes, wages, rent Objective: maximize benefit of location to firm
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What factors should we consider? Skilled workforce Environmental laws / cost of compliance Cost of utilities, labor, taxes Suppliers close by – fast & cheap access Customers close by Competitors close by? Skilled labor pool International - control issues?
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Service Facilities – Traffic focus Revenue changes a huge amount, depending on the location. Old Navy in Stead because of cheap land? Location, 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. Cost probably doesn’t change nearly as much, by location All malls have high rent
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Wal-Mart WinCo Office Max Toys Party
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“I-80 & McCarran” 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
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Cost Focus Revenue does not vary much, depending on the location. Customers don’t care if your warehouse is in Sparks or Sacramento Location is a major cost driver Impacts shipping, labor, production costs Varies greatly by location
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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
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Cost Focus Process Overview 1. Identify general region to locate in Usually based on mostly on transp. costs 2. Identify a list of candidate cities Choose cities with good transp. Access Estimate labor cost & availability, facilities costs 3. Select metro area, identify candidate properties. Find cost of building or leasing individual properties
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Case Study: Importing from China to E. Coast
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Customer Location
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More detail on East Coast possibilities
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Interstate Detail
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New Orleans $3,200 36 days NY / NJ $3,600 36 days Wilmington DE $3,950 36 days (door) Norfolk $3,600 34 days Charleston $3,600 35 days China to U.S. Container Rates Atlanta $3,200 37 days (door)
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Roanoke Norfolk Philadelphia Baltimore Wilmington Allentown Harrisburg 750 850 750 825 Elizabeth, NJ 350 656 375 950 575 305 1125 305 780 375 305 428 888 725 265 343 295 950 Drayage Rates North
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China to Long Beach
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Cincinnati $2925, 21d Columbus $3000, 21days Atlanta $3300, 23d Memphis $2900, 18.5d Murray $3350, 22d Nashville $3300, 22d Louisville $3050, 20d Landbridge Data
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Interstate Access
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Distribution Center Location Minimize demand-weighted distance: distance to each customer times the volume of shipments to the customer How many to build? Where to build?
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Case Study: Retailer Location of a 5 th returns processing facility Addresses of 2125 Continental U.S. stores Location of 4 Return Goods Processing Centers List of all return shipments from each store, including pounds and # pallets Calculated actual highway distances from every store to its DC
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Local Streets
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Transportation Cost Approx. Current Pallets:205,254 Current Pallet Miles: 77.9m Cost / pallet-mile11.68 cents Pallet-Mile = 1 pallet traveling 1 mile Minimize average distance traveled
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Solution Software Some locations must have a facility Considers adding a facility at every existing store We 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
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Current RCs
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Dallas Realignment
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Close 1 existing RDC
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Location Methods 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) Factor Weighting – consider qualitative factors Break-even – Consider fixed & variable costs
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Center of Gravity Compute X and Y coordinates separately d ix is the X coordinate of location i. d iy is the Y coordinate of i. W i is the X demand at i. C X and C Y are the coordinates of the DC.
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Center of Gravity Example 1 You need to decide where to build a new DC for Motorola. It needs to serve wholesalers in Reno, Dallas, and Chicago. Locate these cities on an unscientific, rectangular grid. Grid must maintain relative distances, but X and Y grids could be different.
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020406080100120140160 80 20 40 60 0 100
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Center of Gravity Method CityDemand Reno is at 17, 55100 Fort Worth is at 78, 2090 Chicago is at 110, 65.120 Demand is TL/month
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Center of Gravity
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020406080100120140160 80 20 40 60 0 100
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Salina KS North Platte Sharon Springs
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Compromise Solution 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 North Platte NE is at I-80 and 83. Access to Dallas less convenient
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020406080100120140160 80 20 40 60 0 100
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Finalizing City 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 Get estimates of inbound, outbound trucking costs. Provide lists of # loads per year to each destination, from each source
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Center of Gravity Example 2 You need to decide where to locate a DC in South Dakota XYDemand Pierre784750 Watertown150658 Sioux Falls1602590 Rapid 124260
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020406080100120140160 80 20 40 60 0 100
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Center of Gravity
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020406080100120140160 80 20 40 60 0 100
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Ardalan Heuristic 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.
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Ardalan Heuristic Minimize weighted distance traveled To FromABCDDem.Weight A011812101.1 B11010781.4 C81009200.7 D9.5790121.0
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Ardalan Method Expected demand at each location. Weight represents importance of serving location (bigger = more important) Step 1: Multiply distances * weights * demand A to B: 11 * 1.1 * 10 = 121
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Ardalan Method Step 2. Add up values in columns FromABCD A012188132 B123.2011278.4 C1121400126 D114841080 349.2345308336.4
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Ardalan Method Choose smallest value as first site. FromABCD A012188132 B123.2011278.4 C1121400126 D114841080 349.2345308336.4
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Ardalan Method 3. If larger, set each cost equal to cost in same row in the chosen column FromABCD A0888888 B112011278.4 C0000 D108841080 220172308166.4
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Ardalan Method Get rid of previously chosen column. Sum, choose smallest sum. FromABD A08888 B112078.4 C000 D108840 220172166.4
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Ardalan Method Repeat 3 & 4 until enough sites chosen. FromABD A08888 B78.4078.4 C000 D000 78.488166.4
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Ardalan Method Repeat 3 & 4 until enough sites chosen. FromAB A088 B78.40 C00 D00 78.488
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Ardalan Summary What we decided is that if we only want to build one location, it should be in C. If we want to build two, they should be in C and D. If we add a third one, it should be in A.
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Ardalan Summary 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.
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P-Median Problem Minimize average weighted distance to customers, when locating P facilities, where P>=1. Can consider 100s of locations. Complex to solve – there is software for this.
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Maximum Covering Problem A facility can “cover” a customer if the customer is within X miles of the facility. Try to find the best location, and minimum number of facilities to cover all demands. Cover a table with plates. Math also very hard.
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Comparison of Results Number of Facilities Demand Covered (Using Distances of 150, 200, 250,250)
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Solving large problems
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Incremental or clean-slate apprach Take into account existing facilities What is the best location to add, given the existing facilities? What is the best to add, if we were to close down one of the current facilities? Unfortunately, only P-Median or Maximum Covering can deal with these.
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Factor Rating Method 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”
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Factor Rating Example 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
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Factor Rating Example Using a scoring system we developed, we have the following. FactorWeightTXCO Transportation0.59001,023 Plant Lease Cost0.34539 Labor availability0.2108 Quality of Life0.179.5
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Normalizing Scores All factors must be scored on the same scale, like 1-10, or 0-1.0, etc. Costs need to be re-scaled Lowest cost site gets a 10. More expensive site gets 39/45 * 10 or 900/1,023 * 10
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Factor Rating Example TXCO FactorWtRawWtdRaw Wtd Tr0.4104.008.803.52 Plant 0.38.72.61103.00 Labor0.2102.0081.60 Q Life0.170.709.50.95 TOTAL9.319.07 TX is best
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Possible Approach Use Ardalan to find out which general regions to locate in (state / county). Use factor weighting to choose city. Ardalan has disadvantage of choosing weights -- difficult to set levels.
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Break-Even Analysis 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
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Locating Service Facilities Using Linear Regression Collect data about your current facilities Use regression to determine which variables have a significant impact on profits Choose new facilities which have these characteristics
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Method Comparison Center of gravity minimizes average distance for one facility only. Ardalan Minimizes weighted distances for more than one facility. Breakeven: fixed & variable costs. Factor weighting considers many other important aspects of location, but does not minimize distance.
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Transportation Method You have 3 DCs, and need to deliver product to 4 customers. Find cheapest way to satisfy all demand A 10 B 10 C 10 D 2 E 4 F 12 G 11
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Solving Transportation Problems Trial and Error Linear Programming – ooh, what’s that?! Tell me more! DEFG A10987 B 1145 C8748
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