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Facility Location. Class 2 and/or 3. Objectives. Identify some of the main reasons organizations need to make location decisions Explain why location decisions are important Discuss the options that are available for location decisions
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FacilityLocation Class 2 and/or 3
Objectives • Identify some of the main reasons organizations need to make location decisions • Explain why location decisions are important • Discuss the options that are available for location decisions • Give examples of the major factors that affect location decisions • Outline the decision process for making these kinds of decisions • Use the techniques presented to solve typical problems
Facility Location Problem • Itis difficult to find a single location with all requiredcharacteristics at the desired level • Forexample: • A locationin Besiktasmay offer a highly skilled labor pool and proximity to customers but land costs may be too high. • Similarly, another location may offer low tax rates and minimal government regulations but may be too far from raw materials source or customer base. • Thus, facility location problem becomes one of selecting site (among several available alternatives) that optimizes a weighted set of objectives.
Logistics Management • Logistics management is the management of a series of macro-level transportation and distribution activities with the main objective of delivering the right amount of material (goods) at the right place at the right time at the right cost using the right methods. • Goods: Raw materials Subassemblies obtained from suppliers Products shipped from plants to warehouses or customers • Logistics management problems can be classified into three categories:
What are these Categories: • Location Problems: Location Problems involve determining the location of one or more new facilities in one or more of several potential sites. The cost of locating each new facility at each of the potential sites is assumed to be unknown+operating and transportation cost of serving customers from this facility-site combination. • Allocation Problems: Allocation Problems assume that the number and location of facilitiesare knownand attempt to determine how each customer is to be served. That is, given • demand for goods at each customer center, • the production or supply • capacities at each facility, and • the cost of serving each customer from each facility, • the allocation problem determined how much each facility is to supply to each customer center. • Location – Allocation Problems: Location – Allocation Problems involve determining not only how much each customer is to receive from each facility but also the number of facilities along with their locations and capacities.
Response Time 1 week-> 1 Distribution Center Clientes Centro distribución
Response Time 5 days-> 2 Distribution Center Clientes Centro distribución
Response Time 3 days-> 5 Distribution Center Clientes Centro distribución
Response Time 1 day-> 13 Distribution Center Clientes Centro distribución
Same Day Response --> 26 Distribution Centers Customer DC
Response time vs. Number of facilities Response Time Number of Facilities
1st Classification of Facility Location Problems • Single-Facility Location Problems Single-Facility location problems deal with the optimal determination of the location of a single facility. • Multi-facility Location Problems Multi-facility location problems deal with the simultaneous location determination for more than one facility. Generally, single-facility location problems are location problems, but Multi-facility location problems can be location as well as location-allocation problems. 2nd Classification of Facility Location Problems This classification of location problems is based on whether the set of possible locations for a facility is finite or infinite: • Continuous Space Location Problem If a facility can be located anywhere within the confines of a geographic area, then the number of possible locations is infinite. • Discrete Space Location Problem Discrete Space Location Problems have a finite feasible set of sites in which to locate a facility.
1st Classification of Facility Location Problems • Single-Facility Location Problems Single-Facility location problems deal with the optimal determination of the location of a single facility. • Multi-facility Location Problems Multi-facility location problems deal with the simultaneous location determination for more than one facility. Generally, single-facility location problems are location problems, but Multi-facility location problems can be location as well as location-allocation problems. 2nd Classification of Facility Location Problems This classification of location problems is based on whether the set of possible locations for a facility is finite or infinite: • Continuous Space Location Problem If a facility can be located anywhere within the confines of a geographic area, then the number of possible locations is infinite. • Discrete Space Location Problem Discrete Space Location Problems have a finite feasible set of sites in which to locate a facility. Because facilities can be located anywhere in a two-dimensional space, sometimes the optimal location provided by the continuous space model may be infeasible. For example, a continuous space model may locate a manufacturing facility on a lake!
3rdClassification of Facility Location Problems • SolutionTechnique: • Minimization • Total cost of settingupandoperatingthenewfacilities (andservingtheusers) • Thesum of distancesto be traveledbytheitems • Thenumber of facilities • Maximization: • Maximizethenumber of customersto be served • Maximizetherevenue of a facility • Minimax: • Minimize themaximumdistancetravelled (eg. emergencyfacilities
Weighted Factor Rating Method Step 1: List all the factors that are important, i.e. have an impact on the location decision. Step 2: Assign appropriate weights (typically between 0 and 1) to each factor based on the relative importance of each. Step 3: Assign a score (typically between 0 and 100) for each location with respect to each factor identified in Step 1. Step 4: Compute the weighted score for each factor for each location by multiplying its weight with the corresponding score (which were assigned Steps 2 and 3, respectively). Step 5: Compute the sum of the weighted scores for each location and choose a location based on these scores.
Example 1: Weighted Factor Method A payroll processing company has recently won several major contracts in the Midwest region of the United States and Central Canada and wants to open a new, large facility to serve these areas. Because customer service is so important, the company wants to be as near its “customers” as possible. A preliminary investigation has shown that Minneapolis, Winnipeg, and Springfield, Illinois are the three most desirable locations, and the payroll company has to select one of these. A subsequent thorough investigation of each location with respect to eight important factors generated the raw scores and weights. Using the location scoring method, determine the best location for the new payroll processing facility.
Steps 1, 2 and 3. Factors and weights for three locations Score Weight 0.25 0.15 0.15 0.10 0.10 0.10 0.08 0.07 Factor Proximity to customer Land and construction prices Wage rates Property taxes Business taxes Commercial travel Insurance costs Office services Minneapolis 95 60 70 70 80 80 70 90 Winnipeg 90 60 45 90 90 65 95 90 Springfield 65 90 60 70 85 75 60 80
Weighted scores for three locations Weighted Score Factor Proximity to customer Land and construction prices Wage rates Property taxes Business taxes Commercial travel Insurance costs Office services Sum of weighted scores Minneapolis 23.75 9.00 10.50 7.00 8.00 8.00 5.60 6.30 78.15 Winnipeg 22.50 9.00 6.75 9.00 9.00 6.50 7.60 6.30 ? Springfield 16.25 13.50 9.00 7.00 8.50 7.50 4.80 5.60 ? Steps 4 and 5.
LOCATION FACTOR WEIGHT Site 1 Site 2 Site 3 Labor pool and climate Proximity to suppliers Wage rates Community environment Proximity to customers Shipping modes Air service .30 .20 .15 .15 .10 .05 .05 80 100 60 75 65 85 50 65 91 95 80 90 92 65 90 75 72 80 95 65 90 Example 2: Weighted Factor Method SCORES (0 TO 100)
Location Factor Rating WEIGHTED SCORES Site 1 Site 2 Site 3 24.00 20.00 9.00 11.25 6.50 4.25 2.50 77.50 19.50 18.20 14.25 12.00 9.00 4.60 3.25 80.80 27.00 15.00 10.80 12.00 9.50 3.25 4.50 82.05 Site 3 has the highest factor rating
Break-Even Analysis Total cost = fixed costs + variable costs (quantity): Revenue = selling price (quantity) Break-even point is where total costs = revenue:
Example 1: Break-Even Analysis A firm estimates that the fixed cost of producing a line of footwear is $52,000 with a $9 variable cost for each pair produced. They want to know: • If each pair sells for $25, how many pairs must they sell to break-even? • If they sell 4000 pairs at $25 each, how much money will they make?
Example 1: Break-Even Analysis cont`d… • Break-even point: • Profit = total revenue – total costs
Example: Break-Even Analysis – Outsourcing Bill & Nancy plan to open a small bagel shop. • The local baker has offered to sell them bagels at 40 cents each. However, they will need to invest $1,000 in bread racks to transport the bagels back & forth from the bakery to their store. • Alternatively, they can bake the bagels at their store for 15 cents each if they invest $15,000 in kitchen equipment. • They expect to sell 60,000 bagels each year. What should they do?
Example: Break-Even Analysis – Outsourcing Interpretation: • They anticipate selling 60,000 bagels (greater than the indifference point of 56,000). • Therefore, make the bagels in-house.
Cost-Profit-Volume Analysis • Steps: • 1.Determine the fixed and variable costs for each alternative • 2.Plot the total-cost lines for all alternatives on the same graph • 3.Determine the location that will have the lowest total cost (or highest profit) for the expected level of output • Assumptions • 1.Fixed costs are constant for the range of probable output • 2.Variable costs are linear for the range of probably output • 3.The required level of output can be closely estimated • 4.Only one product is involved
Cost-Profit-Volume Analysis, cont`d… • For a cost analysis, compute the total cost for each alternative location:
Example:Cost-Profit-Volume Analysis • Fixed and variable costs for four potential plant locations are shown below:
Minimum Cost Method • TCBURSA =11*200+10*200+4*300+9*200+7*100=7900
Minimum Cost Method • TCMERSİN =11*200+10*100+8*100+4*300+1*300=5500
Minimum Cost Method • TCBURSA =11*200+10*200+4*300+9*200+7*300=7900 • TCMERSİN =11*200+10*100+8*200+4*300+1*300=5500
Hybrid Analysis • A disadvantage of the Qualitative method discussed earlier is that location decision is made based entirely on a subjective evaluation. Although Quantitativemethod overcomes this disadvantage, it does not allow us to incorporate unquantifiablefactors that have a major impact on the location decision. • Example: The Quantitative techniques can easily consider: • transportation cost, and • operational costs, but intangible factors such as; • the attitude of a community toward businesses, • potential labor unrest, • reliability of auxiliary service providers are difficult to capture though these are important in choosing a location decision. • Therefore, we need a method that incorporates subjective as well as quantifiablecost and other factors.
Hybrid Analysis • A multi-attribute, single-facility location model based on the ones presented by Brown and Gibson (1972) and Buffa and Sarin (1987). • This model classifies the objective and subjective factors important to the specific location problem being addressed as: • critical, • objective, and • subjective. • The meaning of objective and subjective factors is obvious. The meaning of critical factors needs some discussion.
Hybrid Analysis • In every location decision, usually at least one factor determines whether or not a location will be considered for further evaluation. • For instance, if water is used extensively in a manufacturing process (e.g. a brewery), then a site that does not have an adequate water supply now or in the future is automatically removed from consideration. • This is an example of a critical factor.
Hybrid Analysis • After the factors are classified, they are assigned numeric values:
