Introduction to Operations Research, Volume 1CD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 199
Each such indicating variable is called a nonbasic variable for the corre- sponding basic solution . The resulting conclusions and terminology ( already introduced in Sec . 4.2 ) are summarized next . Each basic solution has m basic ...
Each such indicating variable is called a nonbasic variable for the corre- sponding basic solution . The resulting conclusions and terminology ( already introduced in Sec . 4.2 ) are summarized next . Each basic solution has m basic ...
Page 288
Use this solution to iden- identify the complementary basic solution in the dual problem ? tify the basic variables and the nonbasic variables for the op6.4-1 . Consider the following problem . timal solution of the primal problem .
Use this solution to iden- identify the complementary basic solution in the dual problem ? tify the basic variables and the nonbasic variables for the op6.4-1 . Consider the following problem . timal solution of the primal problem .
Page 311
Feasibility test : Check to see whether all the basic variables are nonnegative . ... This selection is made by checking the nonbasic variables with negative coefficients in that equation ( the one containing the leaving basic variable ) ...
Feasibility test : Check to see whether all the basic variables are nonnegative . ... This selection is made by checking the nonbasic variables with negative coefficients in that equation ( the one containing the leaving basic variable ) ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero
Bibliographic information
| Title | Introduction to Operations Research, Volume 1 Introduction to Operations Research, Frederick S. Hillier McGraw-Hill industrial & plant engineering series McGraw-Hill series in industrial engineering and management science |
| Authors | Frederick S. Hillier, Gerald J. Lieberman |
| Edition | 7, illustrated |
| Publisher | McGraw-Hill, 2001 |
| Original from | the University of Michigan |
| Digitized | 8 Aug 2011 |
| ISBN | 0072321695, 9780072321692 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |