Facility location
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Facility Location. Operations Management Dr. Ron Tibben-Lembke. 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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Facility location

Facility Location

Operations Management

Dr. Ron Tibben-Lembke


Location decisions

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


What factors should we consider

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?


Service facilities traffic focus

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


Facility location

Wal-Mart

Toys

Party

Office

Max

WinCo


A tale of two stores

A Tale of Two Stores

W

K


Facility location

  • “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


Cost focus

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


Cost minimization

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

Cost Focus Process Overview

  • Identify general region to locate in

    • Usually based on mostly on transp. costs

  • Identify a list of candidate cities

    • Choose cities with good transp. Access

    • Estimate labor cost & availability, facilities costs

  • Select metro area, identify candidate properties.

    • Find cost of building or leasing individual properties


Case study importing from china to e coast

Case Study:Importing from China to E. Coast


Customer location

Customer Location


Facility location

Interstate

Detail


China to u s container rates

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

Atlanta

$3,200

37 days (door)

New Orleans $3,200

36 days


Facility location

Allentown

305

575

428

DrayageRates

North

Elizabeth, NJ

850

Harrisburg

295

343

350

Philadelphia

305

265

375

850

Wilmington

656

825

750

Baltimore

305

375

750

780

950

1125

725

950

888

Roanoke

750

Norfolk


China to long beach

China to Long Beach


Landbridge data

Landbridge Data

Columbus $3000, 21days

Cincinnati $2925, 21d

Louisville $3050, 20d

Murray $3350, 22d

Nashville

$3300, 22d

Memphis $2900, 18.5d

Atlanta $3300, 23d


Distribution center location

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?


Case study retailer

Case Study: Retailer

  • Location of a 5th 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


Local streets

Local Streets


Transportation cost approx

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


Solution software

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


Current rcs

Current RCs


Dallas realignment

Dallas Realignment


Facility location

Close 1 existing RDC


Location methods

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


Center of gravity

Center of Gravity

  • 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

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.


Facility location

100

80

60

40

20

0

020406080100120140160


Center of gravity method

Center of Gravity Method

CityXYDemand

  • Reno is at 17, 55100

  • Dallas is at 78, 2090

  • Chicago is at 110, 65120

  • Demand is TL/month


Center of gravity1

Center of Gravity


Facility location

100

80

60

40

20

0

020406080100120140160


Facility location

North

Platte

Sharon

Springs

Salina KS


Compromise solution

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


Facility location

100

80

60

40

20

0

020406080100120140160


Finalizing city

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


Center of gravity example 2

Center of Gravity Example 2

  • You need to decide where to locate a DC in South Dakota

    XYDemand

  • Pierre784750

  • Watertown150658

  • Sioux Falls1602590

  • Rapid 124260


Facility location

100

80

60

40

20

0

020406080100120140160


Center of gravity2

Center of Gravity


Facility location

100

80

60

40

20

0

020406080100120140160


Ardalan heuristic

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.


Ardalan heuristic1

Ardalan Heuristic

  • Minimize cost (distance) traveled

    From

    ToABCDDem.

    A01181210

    B1101078

    C8100920

    D9.579012

The distance from A to A is shown as 0, but there is no reason we couldn’t put the actual mileage in.

Carriers might charge more on popular routes, so costs may not be symmetrical.

Cost to serve A from D is $12.

Cost to serve D from A is $9.5.


Ardalan method

Ardalan Method

  • Expected demand at each location.

  • Step 1: Multiply distances * demand

  • A to B: 11 * 10 = 110


Ardalan heuristic2

Ardalan Heuristic

  • Multiply distances times demand, and sum

    ToABCD*Dem =ABCD

    A011812*10011080120

    B110107*88808056

    C81009*201602000180

    D9.5790*12114841080

    Total362394268356


Ardalan heuristic3

Ardalan Heuristic

  • Choose smallest total as first location

    ABCD

    A011080120

    B8808056

    C1602000180

    D114841080

    Total362394268356

If we only build one facility, we should build it in C, and the total transportation costs will be 268. (This is in dollars, or truckload miles, or whatever the units in the table were.)

Notice that even if we built a facility in B or D, it will continue to be cheaper to serve A from C.

In the next step, we will make use of that.


Ardalan heuristic4

Ardalan Heuristic

  • Compare each cost in row to the cost in the chosen cost, and switch is lower

    ABCD

    A0808080

    B8008056

    C0000

    D108841080

    Total188164268136

Why do we do that?

Before, the first row said

“0, 110, 80, 120.”

We’ve decided to build in C

If we build in A, B, or D, how much will we spend to haul to A? No matter what, we’ll spend 80.

If we locate in D, we’ll serve B from D, but otherwise, we’ll serve B from C, because it’s cheaper.


Ardalan heuristic5

Ardalan Heuristic

  • Don’t need first chosen city any more.

  • Choose second cheapest city

    ABD

    A08080

    B80056

    C000

    D108840

    Total188164136

This means that if we locate #2 in D (and we already decided to locate one in C), total costs will be $136. How?

A served at cost of $80 by C.

B served at cost of $56 by D.

C served at cost of $0 by C.

D served at cost of $0 by D.

This is why we needed to change the costs above.


Ardalan heuristic6

Ardalan Heuristic

  • Compare non-chosen cities’ costs to cost of chosen, and choose the lower cost

    From ABD

    A08080

    B56056

    C000

    D000

    Total5680136


Ardalan heuristic7

Ardalan Heuristic

  • Compare non-chosen cities’ costs to cost of chosen, and choose the lower cost

    From AB

    A080

    B560

    C00

    D00

    Total5680

If we locate the third facility in A, we will have facilities in C, D, and A. B is the only city without a DC, and it will be served at a cost of $56.

What happens if we do the method one more time?


Ardalan heuristic8

Ardalan Heuristic

  • Compare non-chosen cities’ costs to cost of chosen, and choose the lower cost

    From AB

    A00

    B560

    C00

    D00

    Total560

After we get rid of the now-unnecessary column A, there is only column B, with total costs of 0.

Does that make sense? Well, yes: every city gets served by the DC located in that city, so if the cost of serving a city from that city is 0, then yes, it makes sense.


Ardalan summary

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.


Ardalan summary1

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.


P median problem

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.


Maximum covering problem

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.


Comparison of results

Comparison of Results

(Using Distances of 150, 200, 250,250)

Demand Covered

Number of Facilities


Solving large problems

Solving large problems


Incremental or clean slate apprach

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.


Factor rating method

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”


Factor rating example

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


Factor rating example1

Factor Rating Example

  • Using a scoring system we developed, we have the following.

    FactorWeightTXCO

    Transportation0.59001023

    Plant Lease Cost0.34539

    Labor availability0.2108

    Quality of Life0.179.5


Normalizing scores

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

      • Plant Lease: 39/45 * 10 = 8.7

      • Transportation: 900/1,023 * 10 = 8.8

  • Multiply these raw scores by the weights for weighted scores


Factor rating example2

Factor Rating Example

TXCO

FactorWtRawWtdRaw Wtd

Transp.0.4104.008.803.52

Plant 0.38.72.61103.00

Labor0.2102.0081.60

Q Life0.170.709.50.95

TOTAL9.319.07

TX is best, but not by a huge amount


Possible approach

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.


Break even analysis

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

  • Hey – this sounds familiar!


Locating service facilities

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


Method comparison

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.


Transportation method

Transportation Method

You have 3 DCs, and need to deliver product to 4 customers.

Find cheapest way to satisfy all demand

D 2

A 10

E 4

B 10

F 12

C 10

G 11


Solving transportation problems

Solving Transportation Problems

  • Trial and Error

  • Linear Programming – ooh, what’s that?!

  • Tell me more!


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