CASE STUDY 4.4 Linear Programming Simplex Method Nicanor Processing Company produces an insecticide for rice and corn farmers. It has two processing plants with different production capacities. The maximum production capacity of Plant A in a week is 15 drums (200 liters per drum), while the maximum production capacity of Plant B is 20 drums per week. The company aims to produce at least 25 drums of insecticide per week to satisfy the orders of industrial customers. The Department of Environment and Natural Resources (DENR) has determined that the production of this insecticide allows for the release of certain particles in the atmosphere which may be hazardous to the community. Plant A emits 10 pounds of particles for every drum of insecticide, while Plant B emits 15 pounds of particles in the atmosphere for every drum of insecticide produced. DENR imposes a penalty of Php20.00 per pound of particles emitted by Plant A and Php20.00 per pound of particles emitted by Plant B. Using the simplex method, determine the optimal solution. REQUIRED Solution of the following: Improved Objective Function Max Profit Converted Constraints Prepare the following: Table 1. Initial Table Table 2. First Iteration Table 3. Second Iteration and so on with the following details: Identify the incoming variable Identify the outgoing variable Create a table to show product, solution quantity, pivot value, and quotient.

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Chapter2: Second-order Linear Odes
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CASE STUDY 4.4 Linear Programming Simplex Method
Nicanor Processing Company produces an insecticide for rice
and corn farmers. It has two processing plants with different
production capacities. The maximum production capacity of
Plant A in a week is 15 drums (200 liters per drum), while the
maximum production capacity of Plant B is 20 drums per week.
The company aims to produce at least 25 drums of insecticide per
week to satisfy the orders of industrial customers. The Department
of Environment and Natural Resources (DENR) has determined
that the production of this insecticide allows for the release of
certain particles in the atmosphere which may be hazardous to
the community. Plant A emits 10 pounds of particles for every
drum of insecticide, while Plant B emits 15 pounds of particles in
the atmosphere for every drum of insecticide produced. DENR
imposes a penalty of Php20.00 per pound of particles emitted by
Plant A and Php20.00 per pound of particles emitted by Plant B.
Using the simplex method, determine the optimal solution.
REQUIRED
Solution of the following:
Improved Objective Function
Max Profit
Converted Constraints
Prepare the following:
Table 1. Initial Table
Table 2. First Iteration
Table 3. Second Iteration and so on with the following details:
Identify the incoming variable
Identify the outgoing variable
Create a table to show product, solution quantity, pivot value,
and quotient.
Transcribed Image Text:CASE STUDY 4.4 Linear Programming Simplex Method Nicanor Processing Company produces an insecticide for rice and corn farmers. It has two processing plants with different production capacities. The maximum production capacity of Plant A in a week is 15 drums (200 liters per drum), while the maximum production capacity of Plant B is 20 drums per week. The company aims to produce at least 25 drums of insecticide per week to satisfy the orders of industrial customers. The Department of Environment and Natural Resources (DENR) has determined that the production of this insecticide allows for the release of certain particles in the atmosphere which may be hazardous to the community. Plant A emits 10 pounds of particles for every drum of insecticide, while Plant B emits 15 pounds of particles in the atmosphere for every drum of insecticide produced. DENR imposes a penalty of Php20.00 per pound of particles emitted by Plant A and Php20.00 per pound of particles emitted by Plant B. Using the simplex method, determine the optimal solution. REQUIRED Solution of the following: Improved Objective Function Max Profit Converted Constraints Prepare the following: Table 1. Initial Table Table 2. First Iteration Table 3. Second Iteration and so on with the following details: Identify the incoming variable Identify the outgoing variable Create a table to show product, solution quantity, pivot value, and quotient.
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