9.4 THE SIMPLEX METHOD: MINIMIZATION


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1 SECTION 9 THE SIMPLEX METHOD: MINIMIZATION 59 The accounting firm in Exercise raises its charge for an audit to $5 What number of audits and tax returns will bring in a maximum revenue? In the simplex method, it may happen that in selecting the departing variable all the calculated ratios are negative This indicates an unbounded solution Demonstrate this in Exercises and Maximize) Maximize) Objective function: Objective function: z x x z x x x x x x x x x x 5 x, x x, x 5 If the simplex method terminates and one or more variables not in the final basis have bottomrow entries of zero, bringing these variables into the basis will determine other optimal solutions Demonstrate this in Exercises 5 and 5 Maximize) Maximize) Objective function: Objective function: z 5x z x x x x 5x 5 x x 5x x x x 5 x, x x, x C 7 Use a computer to maximize the objective function z x 7x x x x 7x 8x 5x 5 x 7x 8x x 9 5x 7x x x 8 where x, x, x, x C 8 Use a computer to maximize the objective function z x x x x subject to the same set of constraints given in Exercise 7 9 THE SIMPLEX METHOD: MINIMIZATION In Section 9, we applied the simplex method only to linear programming problems in standard form where the objective function was to be maximized In this section, we extend this procedure to linear programming problems in which the objective function is to be minimized A minimization problem is in standard form if the objective function w c x c x c n x n is to be minimized, a x a x a n x n b a x a x a n x n b a m x a m x a mn x n b m where x i and b i The basic procedure used to solve such a problem is to convert it to a maximization problem in standard form, and then apply the simplex method as discussed in Section 9 In Example 5 in Section 9, we used geometric methods to solve the following minimization problem
2 5 CHAPTER 9 LINEAR PROGRAMMING Minimization Problem: Find the minimum value of w x 5x Objective function subject to the following constraints x x x x x x 9 } Constraints where x and x The first step in converting this problem to a maximization problem is to form the augmented matrix for this system of inequalities To this augmented matrix we add a last row that represents the coefficients of the objective function, as follows 5 9 Next, we form the transpose of this matrix by interchanging its rows and columns 9 5 Note that the rows of this matrix are the columns of the first matrix, and vice versa Finally, we interpret the new matrix as a maximization problem as follows To do this, we introduce new variables, y, y, and y ) We call this corresponding maximization problem the dual of the original minimization problem Dual Maximization Problem: Find the maximum value of z y y 9y Dual objective function y y y Dual constraints y y y 5 } where y, y, and y As it turns out, the solution of the original minimization problem can be found by applying the simplex method to the new dual problem, as follows
3 SECTION 9 THE SIMPLEX METHOD: MINIMIZATION 5 y y y s s b Variables s Departing 5 s y y y s s b Variables 5 y s Departing 5 y y y s s b Variables y y 9 x x Thus, the solution of the dual maximization problem is z 5 This is the same value we obtained in the minimization problem given in Example 5, in Section 9 The xvalues corresponding to this optimal solution are obtained from the entries in the bottom row corresponding to slack variable columns In other words, the optimal solution occurs when x and x The fact that a dual maximization problem has the same solution as its original minimization problem is stated formally in a result called the von Neumann Duality Principle, after the American mathematician John von Neumann 9 957) Theorem 9 The von Neumann Duality Principle The objective value w of a minimization problem in standard form has a minimum value if and only if the objective value z of the dual maximization problem has a maximum value Moreover, the minimum value of w is equal to the maximum value of z Solving a Minimization Problem We summarize the steps used to solve a minimization problem as follows
4 5 CHAPTER 9 LINEAR PROGRAMMING Solving a Minimization Problem A minimization problem is in standard form if the objective function w c x c x c n x n is to be minimized, a x a x a n x n b a x a x a n x n b a m x a m x a mn x n b m where x i and b i To solve this problem we use the following steps Form the augmented matrix for the given system of inequalities, and add a bottom row consisting of the coefficients of the objective function a a a m c Form the transpose of this matrix a a a n b a a a m c a a a n b a n a n a mn c n a m a m a mn b m Form the dual maximization problem corresponding to this transposed matrix That is, find the maximum of the objective function given by z b y b y b m y m a y a y a m y m c a y a y a m y m c a n y a n y a mn y m c n b b b m c c c n where y, y,, and y m Apply the simplex method to the dual maximization problem The maximum value of z will be the minimum value of w Moreover, the values of x, x,, and x n will occur in the bottom row of the final simplex tableau, in the columns corresponding to the slack variables
5 SECTION 9 THE SIMPLEX METHOD: MINIMIZATION 5 We illustrate the steps used to solve a minimization problem in Examples and EXAMPLE Solving a Minimization Problem Find the minimum value of w x x Objective function x x x x } Constraints where x and x Solution The augmented matrix corresponding to this minimization problem is Thus, the matrix corresponding to the dual maximization problem is given by the following transpose This implies that the dual maximization problem is as follows Dual Maximization Problem: Find the maximum value of z y y Dual objective function y y Dual constraints y y } where y and y We now apply the simplex method to the dual problem as follows y y s s b Variables s Departing s
6 5 CHAPTER 9 LINEAR PROGRAMMING y y s s b Variables y s Departing 9 y y s s b Variables y y x x From this final simplex tableau, we see that the maximum value of z is Therefore, the solution of the original minimization problem is w Minimum Value and this occurs when x and x Both the minimization and the maximization linear programming problems in Example could have been solved with a graphical method, as indicated in Figure 99 Note in Figure 99 a) that the maximum value of z y y is the same as the minimum value of w x x, as shown in Figure 99 b) See page 55) EXAMPLE Solving a Minimization Problem Find the minimum value of w x x 8x x x x } x x x 8 x x x Objective function Constraints where x, x, and x
7 SECTION 9 THE SIMPLEX METHOD: MINIMIZATION 55 Figure 99 a), ) y, ), b) 5 x Maximum: z = y + y =, ), ) Minimum: w = x + x =, ), ) 5 Solution x y The augmented matrix corresponding to this minimization problem is 8 Thus, the matrix corresponding to the dual maximization problem is given by the following transpose This implies that the dual maximization problem is as follows Dual Maximization Problem: Find the maximum value of z y 8y y y x y y y y y y y 8 Dual objective function Dual constraints where y, y, and y We now apply the simplex method to the dual problem as follows y y y s s s b Variables s s 8 s Departing 8 y y y s s s b Variables s Departing 8 } 8 8 s y
8 5 CHAPTER 9 LINEAR PROGRAMMING y y y s s s b Variables y 5 s y x x x From this final simplex tableau, we see that the maximum value of z is Therefore, the solution of the original minimization problem is w and this occurs when Minimum Value x, x, and x Applications EXAMPLE A Business Application: Minimum Cost A small petroleum company owns two refineries Refinery costs $, per day to operate, and it can produce barrels of highgrade oil, barrels of mediumgrade oil, and barrels of lowgrade oil each day Refinery is newer and more modern It costs $5, per day to operate, and it can produce barrels of highgrade oil, barrels of mediumgrade oil, and 5 barrels of lowgrade oil each day The company has orders totaling 5, barrels of highgrade oil, 7, barrels of mediumgrade oil, and, barrels of lowgrade oil How many days should it run each refinery to minimize its costs and still refine enough oil to meet its orders? Solution To begin, we let x and x represent the number of days the two refineries are operated Then the total cost is given by C,x 5,x The constraints are given by Highgrade) x x 5, } Mediumgrade) x x 7, Lowgrade) x 5x, Objective function Constraints where x and x problem is The augmented matrix corresponding to this minimization
9 SECTION 9 THE SIMPLEX METHOD: MINIMIZATION 57, 5 5, 5, 7,, The matrix corresponding to the dual maximization problem is 5, 7, 5,, 5, We now apply the simplex method to the dual problem as follows y y y s s b Variables, s 5 5, s Departing 5, 7,, y y y s s b Variables 8, s Departing 5 5 7, 5, 5 5 y,5, y y y s s b Variables y 8 5 y ,75, x x From the third simplex tableau, we see that the solution to the original minimization problem is 5 7 7
10 58 CHAPTER 9 LINEAR PROGRAMMING C $,75, Minimum cost and this occurs when x 5 and x 5 Thus, the two refineries should be operated for the following number of days Refinery : 5 days Refinery : 5 days Note that by operating the two refineries for this number of days, the company will have produced the following amounts of oil Highgrade oil: Mediumgrade oil: Lowgrade oil: 5 5 5, barrels 5 5 7,5 barrels 5 5 5, barrels Thus, the original production level has been met with a surplus of 5 barrels of mediumgrade oil) SECTION 9 EXERCISES In Exercises, determine the dual of the given minimization problem Objective function: Objective function: w x x w x x x x x x 5x x 9 x x x, x x, x Objective function: Objective function: In Exercises 7, a) solve the given minimization problem by the graphical method, b) formulate the dual problem, and c) solve the dual problem by the graphical method 7 Objective function: 8 Objective function: w x x w x x x x x x x x 5 7x x x, x x, x w x x x x x x x x x 8x x x 8x x, x, x w 9x x x x 5 x x 8 x x x, x 5 Objective function: Objective function: x, 5, ), ) x x,, ), ) x w x x x w 9x x x x x x 9 x x x 7 x x x x x x x, x, x x, x, x
11 SECTION 9 EXERCISES 59 9 Objective function: Objective function: 5 Objective function: Objective function: w x x w x x w x x w x x x x x x x x x x 9 x, x x, x x x, ), 5 x 8, ), ) 8 x 5x x 9 x x x x x x x, x x, x 7 Objective function: 8 Objective function: w 8x x x w 8x x 8x x x x x x x x x x 7 x x x x x x 8 x x x 8 x, x, x x, x, x 9 Objective function: Objective function: Objective function: Objective function: w x x w x x x x x x x, x x, ), x x 5 x x x, x In Exercises, solve the given minimization problem by solving the dual maximization problem with the simplex method Objective function: Objective function: w x w x 8x x 5x x 5x x, x 5 x 8 x, 5), ) x 7x 9 x x x, x x w x x x x x x 8 x x x x x x x, x, x w x 5x 7x x x 7x 5 x x x 8 x x x x, x, x In Exercises, two dietary drinks are used to supply protein and carbohydrates The first drink provides unit of protein and units of carbohydrates in each liter The second drink supplies units of protein and units of carbohydrates in each liter An athlete requires units of protein and 5 units of carbohydrates Find the amount of each drink the athlete should consume to minimize the cost and still meet the minimum dietary requirements The first drink costs $ per liter and the second costs $ per liter The first drink costs $ per liter and the second costs $ per liter The first drink costs $ per liter and the second costs $ per liter The first drink costs $ per liter and the second costs $ per liter In Exercises 5 8, an athlete uses two dietary drinks that provide the nutritional elements listed in the following table Drink Protein Carbohydrates Vitamin D I II 5
12 5 CHAPTER 9 LINEAR PROGRAMMING Find the combination of drinks of minimum cost that will meet the minimum requirements of units of protein, units of carbohydrates, and units of vitamin D 5 Drink I costs $5 per liter and drink II costs $8 per liter Drink I costs $7 per liter and drink II costs $ per liter 7 Drink I costs $ per liter and drink II costs $5 per liter 8 Drink I costs $8 per liter and drink II costs $ per liter 9 A company has three production plants, each of which produces three different models of a particular product The daily capacities in thousands of units) of the three plants are as follows Model Model Model Plant 8 8 Plant Plant 8 The total demand for Model is, units, for Model is 7, units, and for Model is 9,5 units Moreover, the daily operating cost for Plant is $55,, for Plant is $,, and for Plant is $, How many days should each plant be operated in order to fill the total demand, and keep the operating cost at a minimum? The company in Exercise 9 has lowered the daily operating cost for Plant to $5, How many days should each plant be operated in order to fill the total demand, and keep the operating cost at a minimum? A small petroleum company owns two refineries Refinery costs $5, per day to operate, and it can produce barrels of highgrade oil, barrels of mediumgrade oil, and 5 barrels of lowgrade oil each day Refinery is newer and more modern It costs $, per day to operate, and it can produce barrels of highgrade oil, 5 barrels of mediumgrade oil, and barrels of lowgrade oil each day The company has orders totaling 5, barrels of highgrade oil,, barrels of mediumgrade oil, and, barrels of lowgrade oil How many days should the company run each refinery to minimize its costs and still meet its orders? A steel company has two mills Mill costs $7, per day to operate, and it can produce tons of highgrade steel, 5 tons of mediumgrade steel, and 5 tons of lowgrade steel each day Mill costs $, per day to operate, and it can produce 5 tons of highgrade steel, tons of mediumgrade steel, and tons of lowgrade steel each day The company has orders totaling, tons of highgrade steel, 5, tons of mediumgrade steel, and,5 tons of lowgrade steel How many days should the company run each mill to minimize its costs and still fill the orders? C Use a computer to minimize the objective function w x 5x 5x x 5x x 5x x 5 5x x x x 5x x 5x x 5 5x x 5x 5x 75 where x, x, x, x C Use a computer to minimize the objective function w 5x x 5x x subject to the same set of constraints given in Exercise
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