D 2 3 A 4 Proportion to mix 10 5. Cost (S/b] $2.49 0 Total cost/in (mix) $2.49 Total % in mix 100% 10 100% 10 $3.04 3.04 1.0 $2.99 LP model formulation Objective: Subject to: 1. BTU/ib 2. Ash 3. Moisture 4. Total $2.61 RHS (Requirements) 11.900 5. Non negativity Definitions of decision variables used in the model: 12,20% 9.40% (84:84), constraints (F4 & H4, F9.F11 8 H9 H11), select non negative and simplex L) 8 Constraints LHS (Total in mix) 11500 11800 12200 12100 11900 10 Ash content 13% 10% 12% 12% 11 Moisture content 10% 8% 8% 8% 12 13 Mathematically formulate a linear optimization model for this problem. 14 6. Implement the model on a spreadsheetmulate the colored cells) 15 . Find the optimal solution using Solver (input objective function (36), decision variab 10 20. Young Energy operates a power plant that includes cool-fired boiler to produce team to drive a gen- 18 erator. The company can purchase different types of 19 coals and blend them to meet the requirements for burning in the boilee. The following table shows the 20 characteristics of the different types of coals: BTU/ % Ash % Moisture Coat (Mb) 92 A 11,500 139 52.40 23 11,800 10% 8% 53.04 24 12,200 12% 52.99 D 12.100 12% 8% 52.01 The BTU/pound must be at least 11.900. In addition, the ash content can be at most 12.29 and the mois- ture content at most 9.4%. Develop and solve a lin- car optimization model to find the best cool blend for Young Energy Type 10% 20