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Section 3.2

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sanam
9 diapositives · 279 Views · Jul 31, 2014

Section 3.2. Linear Programming Problems. Linear Programming Problem. A linear programming problem consists of a linear objective function to be maximized or minimized, subject to certain constraints in the form of linear equalities or inequalities.

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Section 3.2
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  1. Section 3.2 Linear Programming Problems

  2. Linear Programming Problem A linear programming problem consists of a linear objective function to be maximized or minimized, subject to certain constraints in the form of linear equalities or inequalities.

  3. Ex. A small company consisting of two carpenters and a finisher produce and sell two types of tables: type A and type B. The type-A table will result in a profit of $50, and each type-B table will result in a profit of $54. A type-A table requires 3 hours of carpentry and 1 hour of finishing. A type-B table requires 2 hours of carpentry and 2 hours of finishing. Each day there are 16 hours available for carpentry and 8 hours available for finishing. How many tables of each type should be made each day to maximize profit?

  4. Organize the Information: Let x = # type A and y= # type B. The Profit to Maximize (in dollars) is given by: P = 50x + 54y

  5. The constraints are given by: Carpentry Finishing Also so that the number of units is not less than 0: So we have:

  6. Ex. A particular company manufactures specialty chairs in two plants. Plant I has an output of at most 150 chairs/month. Plant II has an output has an output of at most 120 chairs/month. The chairs are shipped to 3 possible warehouses - A, B, and C. The minimum monthly requirements for warehouses A, B, and C are 70, 70, and 80 respectively. Shipping charges from plant I (to A, B, and C) are $30, $32, and $38/chair and from plant II (to A, B, and C) are $32, $28, $26. How many chairs should be shipped to each warehouse to minimize the monthly shipping cost?

  7. Organize the Information: Number of Chairs Cost to Ship

  8. We want to minimize the cost function: C = 30x1 + 32x2 + 38x3 + 32x4 + 28x5 + 26x6 Production constraints: Plant I Plant II Warehouse constraints: A B C

  9. So the problem is: Minimize: Subject to: C = 30x1 + 32x2 + 38x3 + 32x4 + 28x5 + 26x6