# W3_Hassan Albarrami_Project location selection using Simple Additive Weighting Technique (SAW)

W3_Hassan Albarrami_Project location selection using Simple Additive Weighting Technique (SAW)

1. Problem Definition.

In my previous blog (w2.1), I made study ended up with preferred alternative which was the one with minimum payback period. The study was from the business point of view. This time I’m going to explore the same alternatives from customer prospective and compare it with my previous blog (W2.1).

In addition to the cost, there are other criteria the customer will look fore to select the suitable place. Simple Additive Weighting Technique (SAW) will be used here to identify the preferred alternative. The maximum yearly profit shown in the table below will be considered as cost this time as it will be the amount the customer should pay yearly to the owner:

Table1: Alternatives and corresponding costs (The numbers are estimated as per local market)

2. Identify the Feasible Alternative.

The following are the alternatives (from blog w2.1);

Three locations are attractive to the visitors in Salalah city

• New Salalah

The below table showing the subjected locations and the criteria I suggested to be studied in this blog (the evaluations given are estimated).

Table2: Alternatives and related criteria

3. Development of the Outcome for Alternative

To use Simple Additive Weighting Technique We need to convert Intangible criteria to non dimensional form. The range from 0 to 1 is used for all values, the scale is shown below:

Table 3. Intangible criteria scale

After substituting the attributes with its corresponding scale the following calculation used to normalize the criteria values and the results are shown in table 4

a)      Whenever large numerical in the rows considered undesirable

rij = (xij Minimum) / (xij)      ………….(2)

b)      Whenever large numerical in the rows considered desirable

rij = (xij) / (xij Maximum)    …………..(2)

Table 4. Result of Non-Dimensional Scaling

The final step is to multiply the results in table 4 by the criterion weight (estimated ), as shown below :

Table 5 Additive Weighting Techniques

4. Selection of the Acceptable Criteria.

By using simple Additive Weighting Technique, the criteria of the feasible alternatives are the highest score.

5. Analysis and Comparison of the Alternative.

From Table 5 Okad is the best in terms of cost and time required to go to work where the customer can save money and time. New salalah is the closest to the city center which means better place for shopping. Similar to Okad, New salalah is close to the main hospital. Saadah and Okad are convenient places where as New salalah is a bit crowded.

6. Selection of the Preferred Alternative.

• As per simple additive method Okad is the best for customer
• As per payback period New salalah is the best for business

Table 6 ( preferred options for customer and bussness)

7. Performance Monitoring and the Post Evaluation of Result.

I believe that New salalah still the best choice for business, however we need to find the optimum building rent so that we can satisfy customer needs and achieve the minimum payback period.

8. References:

1. PMI_ Oman 2014, W2.1_Hassan Albarrami_Project location selection. Retrieved on June 18, 2014

https://pmioman14.wordpress.com/2014/06/15/w2-1_hassan-albarrami_project-location-selection/

1. Valentinas Podvezko (2011), The Comparative Analysis of MCDA Methods SAW and COPRAS. In Inzinerine Ekonomika-Engineering Economics, 2011, 22(2), 134-146. Retrieved on June 18, 2014,from

http://vpa.ktu.lt/index.php/EE/article/viewFile/310/829

1. TRIANUGROHO, A. (2014, March 27). W5_Andi_Decision Making Compensatory Models | Kristal AACE 2014. Retrieved on June 18, 2014, from http://kristalaace2014.wordpress.com/2014/03/27/w5_andi_decision-making-compensatory-models/