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        99790_17_ch17_p001-047.qxd  03/08/2007  04:27 PM  Page 17-1
                                 CHAPTER 17
                  Linear Programming: 
                  Simplex Method
                  CONTENTS
                  17.1 AN ALGEBRAIC OVERVIEW      17.6 TABLEAU FORM: 
                      OF THE SIMPLEX METHOD           THE GENERALCASE
                      Algebraic Properties of the     Greater-Than-or-Equal-to
                       Simplex Method                   Constraints
                      Determining a Basic Solution    Equality Constraints
                      Basic Feasible Solution         Eliminating Negative Right-Hand-
                  17.2 TABLEAU FORM                     Side Values
                                                      Summary of the Steps to Create
                  17.3 SETTING UPTHE INITIAL            Tableau Form
                      SIMPLEX TABLEAU             17.7 SOLVING AMINIMIZATION
                  17.4 IMPROVING THE SOLUTION         PROBLEM
                  17.5 CALCULATING THE NEXT       17.8 SPECIALCASES
                      TABLEAU                         Infeasibility
                      Interpreting the Results of an  Unboundedness
                       Iteration                      Alternative Optimal Solutions
                      Moving Toward a Better Solution Degeneracy
                      Interpreting the Optimal Solution
                      Summary of the Simplex Method
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                              17-2                           Chapter 17      Linear Programming: Simplex Method
                                                             InChapter2weshowedhowthegraphicalsolutionprocedurecanbeusedtosolvelinearpro-
                                                             gramming problems involving two decision variables. However, most linear programming
                                                             problemsaretoolargetobesolvedgraphically,andanalgebraicsolutionproceduremustbe
                                                             employed.Themostwidelyusedalgebraicprocedureforsolvinglinearprogrammingprob-
                                                                                                        1
                                                             lemsiscalledthesimplexmethod. Computerprogramsbasedonthismethodcanroutinely
                                                             solve linear programming problems with thousands of variables and constraints. The Man-
                                                             agement Science inAction, FleetAssignment at DeltaAir Lines, describes solving a linear
                                                             programinvolving60,000variablesand40,000constraintsonadailybasis.
                                                    MANAGEMENT SCIENCE IN ACTION
                                                  FLEETASSIGNMENTATDELTAAIR LINES*
                                                  Delta Air Lines uses linear and integer programming            shows the size of linear programs that can be solved
                                                  in its Coldstart project to solve its fleet assignment         today. The typical size of the daily Coldstart model
                                                  problem. The problem is to match aircraft to flight            is about 60,000 variables and 40,000 constraints.
                                                  legs and fill seats with paying passengers. Airline            The first step in solving the fleet assignment prob-
                                                  profitability depends on being able to assign the right        lem is to solve the model as a linear program. 
                                                  size of aircraft to the right leg at the right time of day.    The model developers report successfully solving
                                                  An airline seat is a perishable commodity; once a              these problems on a daily basis and contend that
                                                  flight takes off with an empty seat the profit poten-          use of the Coldstart model will save Delta Air Lines
                                                  tial of that seat is gone forever. Primary objectives of       $300 million over the next three years.
                                                  the fleet assignment model are to minimize operat-
                                                  ing costs and lost passenger revenue. Constraints are          *Based on R. Subramanian, R. P. Scheff, Jr., J. D.
                                                  aircraft availability, balancing arrivals and depar-           Quillinan, D. S. Wiper, and R. E. Marsten, “Coldstart:
                                                  tures at airports, and maintenance requirements.               Fleet Assignment at Delta Air Lines,” Interfaces
                                                       The successful implementation of the Cold-                (January/February 1994): 104–120.
                                                  start model for assigning fleet types to flight legs
                                                  17.1       AN ALGEBRAIC OVERVIEWOFTHE SIMPLEX METHOD
                                                             Let us introduce the problem we will use to demonstrate the simplex method. HighTech In-
                                                             dustries imports electronic components that are used to assemble two different models of
                                                             personal computers. One model is called the Deskpro, and the other model is called the
                                                             Portable. HighTech’s management is currently interested in developing a weekly produc-
                                                             tion schedule for both products.
                                                                  The Deskpro generates a profit contribution of $50 per unit, and the Portable generates
                                                             a profit contribution of $40 per unit. For next week’s production, a maximum of 150 hours
                                                             of assembly time can be made available. Each unit of the Deskpro requires 3 hours of
                                                             assembly time, and each unit of the Portable requires 5 hours of assembly time. In addi-
                                                             tion, HighTech currently has only 20 Portable display components in inventory; thus, no
                                                             more than 20 units of the Portable may be assembled. Finally, only 300 square feet of ware-
                                                             house space can be made available for new production. Assembly of each Deskpro requires
                                                             8 square feet of warehouse space; similarly, each Portable requires 5 square feet.
                                                             1
                                                              Several computer codes also employ what are called interior point solution procedures. They work well on many large prob-
                                                             lems, but the simplex method is still the most widely used solution procedure.
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                                                                                  17.1       An Algebraic Overview of the Simplex Method                                                                                   17-3
                                                                                        To develop a linear programming model for the HighTech problem, we will use the fol-
                                                                                  lowing decision variables:
                                                                                                                             x number of units of the Deskpro
                                                                                                                               1
                                                                                                                             x2  number of units of the Portable
                                                                                  The complete mathematical model for this problem is presented here.
                                                                                                                  Max 50x 40x                                     
                                                                                                                                   1            2
                                                                                                                  s.t.                                             
                                                                                                                              3x    5x  150  Assembly time
                                                                                                                                   1            2
                                                                                                                                             1x2    20           Portable display
                                                                                                                                8x    5x  300                   Warehouse capacity
                                                                                                                                   1            2
                                                                                                                                  x , x  0
                                                                                                                                   1     2
                                                                                        Adding a slack variable to each of the constraints permits us to write the problem in
                                                                                  standard form.
                                                                                                                     Max 50x 40x 0s 0s 0s                                                                       (17.1)
                                                                                                                                      1            2         1          2          3
                                                                                                                     s.t.                                                                                            
                                                                                                                               3x  5x  1s                                           150                          (17.2)
                                                                                                                                      1            2         1
                                                                                                                                               1x2               1s2                   20                         (17.3)
                                                                                                                                  8x  5x                                  1s  300                                (17.4)
                                                                                                                                      1            2                               3
                                                                                                                                    x , x , s , s , s  0                                                           (17.5)
                                                                                                                                      1    2    1    2    3
                                         The simplex method was                   Algebraic Properties of the Simplex Method
                                         developed by George                      Constraintequations(17.2)to(17.4)formasystemofthreesimultaneouslinearequationswith
                                         Dantzig while working for
                                         the U.S. Air Force. It was               five variables.Wheneverasystemofsimultaneouslinearequationshasmorevariablesthan
                                         first published in 1949.                 equations,wecanexpectaninfinitenumberofsolutions.Thesimplexmethodcanbeviewed
                                                                                  as an algebraic procedure for finding the best solution to such a system of equations. In the
                                                                                  preceding example, the best solution is the solution to equations (17.2) to (17.4) that maxi-
                                                                                  mizestheobjectivefunction(17.1)andsatisfiesthenonnegativityconditionsgivenby(17.5).
                                                                                  Determining a Basic Solution
                                                                                  For the HighTech Industries constraint equations, which have more variables (five) than
                                                                                  equations (three), the simplex method finds solutions for these equations by assigning zero
                                                                                  values to two of the variables and then solving for the values of the remaining three vari-
                                                                                  ables. For example, if we set x2  0 and s1  0, the system of constraint equations becomes
                                                                                                                                        3x1                       150                                              (17.6)
                                                                                                                                               1s                  20                                              (17.7)
                                                                                                                                                     2
                                                                                                                                        8x1            1s3  300                                                   (17.8)
                99790_17_ch17_p001-047.qxd  03/08/2007  04:27 PM  Page 17-4
                                 17-4                              Chapter 17       Linear Programming: Simplex Method
                                                                        Using equation (17.6) to solve for x , we have
                                                                                                                        1
                                                                                                                        3x 150
                                                                                                                           1
                                                                   and hence x  150/3  50. Equation (17.7) provides s  20. Finally, substituting x  50
                                                                                  1                                                         2                                     1
                                                                   into equation (17.8) results in
                                                                                                                  8(50)  1s3  300
                                                                   Solving for s , we obtain s 100.
                                                                                    3                 3
                                 Abasic solution is obtained            Thus, we obtain the following solution to the three-equation, five-variable set of linear
                                 by setting two of the five        equations:
                                 variables equal to zero and
                                 solving the three equations                                                            x         50
                                 simultaneously for the                                                                  1
                                 values of the other three                                                             x2           0
                                 variables. Mathematically,                                                             s1          0
                                 we are guaranteed a                                                                    s         20
                                 solution only if the resulting                                                          2
                                 three equations are linearly                                                           s3  100
                                 independent. Fortunately,
                                 the simplex method is             This solution is referred to as a basic solution for the HighTech linear programming prob-
                                 designed to guarantee that        lem. To state a general procedure for determining a basic solution, we must consider a
                                 a solution exists for the         standard-form linear programming problem consisting of n variables and m linear equa-
                                 basic variables at each           tions, where n is greater than m.
                                 iteration.
                                                                       Basic Solution
                                                                       To determine a basic solution, set n  m of the variables equal to zero, and solve the
                                                                       mlinear constraint equations for the remaining m variables.2
                                                                        In terms of the HighTech problem, a basic solution can be obtained by setting any two
                                                                   variables equal to zero and then solving the system of three linear equations for the re-
                                                                   maining three variables. We shall refer to the n  m variables set equal to zero as the non-
                                                                   basicvariablesandtheremainingmvariablesasthebasicvariables.Thus,inthepreceding
                                                                   example, x and s are the nonbasic variables, and x , s , and s are the basic variables.
                                                                                 2        1                                             1   2        3
                                                                   Basic Feasible Solution
                                                                   Abasic solution can be either feasible or infeasible. Abasic feasible solution is a basic so-
                                                                   lution that also satisfies the nonnegativity conditions. The basic solution found by setting
                                                                   x and s equal to zero and then solving for x , s , and s is not a basic feasible solution be-
                                                                    2        1                                                1   2         3
                                                                   cause s 100. However, suppose that we had chosen to make x and x nonbasic vari-
                                                                            3                                                                                1        2
                                                                   ables by setting x1  0 and x2  0. Solving for the corresponding basic solution is easy
                                                                   because with x  x  0, the three constraint equations reduce to
                                                                                       1      2
                                                                                                                 1s                   150
                                                                                                                    1
                                                                                                                       1s               20
                                                                                                                           2
                                                                                                                                1s3  300
                                                                   2
                                                                    In some cases, a unique solution cannot be found for a system of m equations and n variables. However, these cases will
                                                                   never be encountered when using the simplex method.
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...Ch p qxd pm page chapter linear programming simplex method contents an algebraic overview tableau form of the generalcase properties greater than or equal to constraints determining a basic solution equality feasible eliminating negative right hand side values summary steps create setting upthe initial solving aminimization improving problem calculating next specialcases infeasibility interpreting results unboundedness iteration alternative optimal solutions moving toward better degeneracy inchapterweshowedhowthegraphicalsolutionprocedurecanbeusedtosolvelinearpro gramming problems involving two decision variables however most problemsaretoolargetobesolvedgraphically andanalgebraicsolutionproceduremustbe employed themostwidelyusedalgebraicprocedureforsolvinglinearprogrammingprob lemsiscalledthesimplexmethod computerprogramsbasedonthismethodcanroutinely solve with thousands and man agement science inaction fleetassignment at deltaair lines describes programinvolving variablesand constrai...

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