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Facility Location Class 2 and/or 3 1 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 2 Facility Location Problem It is difficult to find a single location with all required characteristics at the desired level For example: ◦ A location in Besiktas may 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. 3 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: 4 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 facilities are known and 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. 5 Response Time 1 week-> 1 Distribution Center Clientes Centro distribución 6 Response Time 5 days-> 2 Distribution Center Clientes Centro distribución 7 Response Time 3 days-> 5 Distribution Center Clientes Centro distribución 8 Response Time 1 day-> 13 Distribution Center Clientes Centro distribución 9 Same Day Response --> 26 Distribution Centers Customer DC 10 Response Time Response time vs. Number of facilities Number of Facilities 11 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. 12 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. 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 13 a manufacturing facility on a lake! 3rd Classification of Facility Location Problems Solution Technique: ◦ Minimization Total cost of setting up and operating the new facilities (and serving the users) The sum of distances to be traveled by the items The number of facilities ◦ Maximization: Maximize the number of customers to be served Maximize the revenue of a facility ◦ Minimax: Minimize the maximum distance travelled (eg. emergency facilities 14 Histogram Method Cost SuWater Enerji Energy Vergi Tax Transportation Ulaştırma Labor İşçilik 0 A B C Alternatives 15 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. 16 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. 17 Steps 1, 2 and 3. Factors and weights for three locations Score Weight Factor Minneapolis Winnipeg Springfield 0.25 Proximity to customer 95 90 65 0.15 Land and construction prices 60 60 90 0.15 Wage rates 70 45 60 0.10 Property taxes 70 90 70 0.10 Business taxes 80 90 85 0.10 Commercial travel 80 65 75 0.08 Insurance costs 70 95 60 0.07 Office services 90 90 80 18 Steps 4 and 5. Weighted scores for three locations Weighted Score Factor Minneapolis Winnipeg Springfield Proximity to customer 23.75 22.50 16.25 Land and construction prices 9.00 9.00 13.50 Wage rates 10.50 6.75 9.00 Property taxes 7.00 9.00 7.00 Business taxes 8.00 9.00 8.50 Commercial travel 8.00 6.50 7.50 Insurance costs 5.60 7.60 4.80 Office services 6.30 6.30 5.60 Sum of weighted scores 78.15 ? ? 19 Example 2: Weighted Factor Method SCORES (0 TO 100) LOCATION FACTOR Labor pool and climate Proximity to suppliers Wage rates Community environment Proximity to customers Shipping modes Air service WEIGHT Site 1 Site 2 Site 3 .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 Sup ple men t 720 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 Sup ple men t 721 Break-Even Analysis Total cost = fixed costs + variable costs (quantity): TC F VC Q Revenue = selling price (quantity) R SPQ Break-even point is where total costs = revenue: TC R or or Q F VC Q SP Q F SP VC 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? 23 Example 1: Break-Even Analysis cont`d… Break-even point: F $52,000 Q 3250 pairs SP VC $25 $9 Profit = total revenue – total costs P SP Q F VC Q $254000 $52,000 $94000 $12,000 24 Break-Even Analysis – Outsourcing Total Cost of Outsourcin g : TC Buy FCBuy VCBuy Q Total Cost of Insourcing : TC Make FCMake VCMake Q Indifferen ce Point : FCBuy VCBuy Q FCMake VCMake Q 25 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? 26 Example: Break-Even Analysis – Outsourcing Indifferen ce Point Calculatio n : FCBuy VCBuy Q FCMake VCMake Q $1,000 $0.40 Q $15,000 $0.15 Q Solve for Q : Q 56,000 Interpretation: ◦ They anticipate selling 60,000 bagels (greater than the indifference point of 56,000). ◦ Therefore, make the bagels in-house. 27 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 28 Cost-Profit-Volume Analysis, cont`d… For a cost analysis, compute the total cost for each alternative location: 29 Example: Cost-Profit-Volume Analysis Fixed and variable costs for four potential plant locations are shown below: 30 Example: Cost-Profit-Volume Analysis, cont`d… 31 Example: Cost-Profit-Volume Analysis, cont`d… 32 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 12 200 ADANA 10 7 9 400 KONYA 8 4 7 400 CAPACITY 400 300 300 1000 33 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 12 200 ADANA 10 7 9 400 KONYA 8 4 7 400 CAPACITY 400 300 300 1000 300 34 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 200 ADANA 10 7 x 9 400 KONYA 8 4 300 7 400 CAPACITY 400 300 300 1000 35 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 200 ADANA 10 7 x 9 400 KONYA 8 4 300 7 CAPACITY 400 300 300 100 400 1000 36 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 200 ADANA 10 7 x 9 400 KONYA 8 4 300 7 CAPACITY 400 x 300 300 100 400 1000 37 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 200 ADANA 10 7 x 9 200 400 KONYA 8 4 300 7 100 400 CAPACITY 400 x 300 300 1000 38 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 x 200 ADANA 10 7 x 9 200 400 KONYA 8 4 300 7 100 400 CAPACITY 400 x 300 300 1000 39 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 8 x 12 x 200 ADANA 10 200 7 x 9 200 400 KONYA 8 x 4 300 7 100 400 CAPACITY 400 300 300 1000 40 Minimum Cost Method İSTANBU L ANKARA BURSA DEMAND TRABZON 11 200 8 x 12 x 200 ADANA 10 200 7 x 9 200 400 KONYA 8 x 4 300 7 100 400 CAPACITY 400 300 300 1000 • TCBURSA =11*200+10*200+4*300+9*200+7*100=7900 41 Minimum Cost Method İSTANBUL ANKARA MERSİN DEMAND TRABZON 11 8 10 200 ADANA 10 7 1 400 KONYA 8 4 6 400 CAPACITY 400 300 300 1000 42 Minimum Cost Method İSTANBUL ANKARA MERSİN DEMAND TRABZON 11 8 10 x 200 ADANA 10 7 1 300 400 KONYA 8 4 6 x 400 CAPACITY 400 300 300 1000 43 Minimum Cost Method İSTANBUL ANKARA MERSİN DEMAND TRABZON 11 8 x 10 x 200 ADANA 10 7 x 1 300 400 KONYA 8 4 300 6 x 400 CAPACITY 400 300 300 1000 44 Minimum Cost Method İSTANBUL ANKARA MERSİN DEMAND TRABZON 11 200 8 x 10 x 200 ADANA 10 100 7 x 1 300 400 KONYA 8 100 4 300 6 x 400 CAPACITY 400 300 300 1000 • TCMERSİN =11*200+10*100+8*100+4*300+1*300=5500 45 Minimum Cost Method İSTANBUL ANKARA BURSA DEMAND TRABZON 11 200 8 x 12 x 200 ADANA 10 200 7 x 9 200 400 KONYA 8 x 4 300 7 100 400 CAPACITY 400 300 300 1000 • TCBURSA =11*200+10*200+4*300+9*200+7*300=7900 İSTANBUL ANKARA MERSİN DEMAND TRABZON 11 200 8 x 10 x 200 ADANA 10 100 7 x 1 300 400 KONYA 8 100 4 300 6 x 400 CAPACITY 400 300 300 1000 • TCMERSİN =11*200+10*100+8*200+4*300+1*300=5500 46 Hybrid Analysis A disadvantage of the Qualitative method discussed earlier is that location decision is made based entirely on a subjective evaluation. Although Quantitative method overcomes this disadvantage, it does not allow us to incorporate unquantifiable factors 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 quantifiable cost and other factors. 47 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. 48 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. 49 Hybrid Analysis After the factors are classified, they are assigned numeric values: 50 Hybrid Analysis Assume that we have m candidate locations and p critical, q objective and r subjective factors. We can determine overall critical factor measure (CFMi), objective factor measure (OFMi), and Subjective Factor Measure (SFMi) for each location i with these equations. 51 Hybrid Analysis After LMi is determined for each candidate location, the next step is to select the one with the greatest LMi value 52 Example: Hybrid Analysis Mole-Sun Brewing Company is evaluating six candidate location; Montreal, Plattsburgh, Ottawa, Albany, Rochester, and Kingston for a new brewery. The two critical, three objective and four subjective factors that management wishes to incorporate in its decision making are summarized in the table (next slide). The weights of the subjective factors are also provided in the table. Determine the best location if the subjective factors are to be weighted 50% more than the objective factors. 53 Questions? 54