The eleven competing robotic R&D/Manufacturing projects are given code names P1 to P11. Each project is associated with a single new product that could be developed by R&D, with a prototype to be built by Manufacturing. The following is known for each project: a. The projected two year R&D and initial manufacturing cost. b. The estimated five year NPV. c. The R&D division's estimate of the probability of success of making the new product. d. The marketing division's qualitative estimate of the new product's ability to capture a 35% market share. The ATP Committee has allocated a budget of $400,000 to the eleven projects. The problem is to select the most beneficial subset of the eleven projects that does not exceed the total budget. The data for this example are given in the following Table. Assume that Cost (criterion)is twice important than NPV, and NPV is twice important than Probability of success and Market share. Project P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 Cost (S) 30,000 40,000 65,000 95,000 100,000 125,000 145,000 165,000 170,000 185,000 200,000 NPV (S) 425,000 380,000 400,000 250,000 900,000 800,000 1,000,000 750,000 800,000 950,000 850,000 Prob. success 0.50 0.75 0.25 1.00 0.25 0.75 0.50 0.50 0.75 0.50 0.75 1. Use appropriate method to find the weight of each criterion 2. Use SAW method to rank alternatives 3. Use TOPSIS method to rank alternatives 4. Do sensitivity analysis for TOPSIS method Market share Good Low High Good Good Fair Fair High Good Fair High a. Scenario 1: all criteria has the same weight b. Scenario 2: cost is the most important criteria and the weight for that is 0.5.