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 115
The slack variable for this constraint is defined to be x3 = 4 – x1 , which is the amount of slack in the left - hand side of the inequality . Thus , Xi + X3 = 4 . Given this equation , xi s 4 if and only if 4 – xy = x3 2 0.
The slack variable for this constraint is defined to be x3 = 4 – x1 , which is the amount of slack in the left - hand side of the inequality . Thus , Xi + X3 = 4 . Given this equation , xi s 4 if and only if 4 – xy = x3 2 0.
Page 216
Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack variables in the final tableau will reveal how this tableau has been obtained from the initial tableau .
Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack variables in the final tableau will reveal how this tableau has been obtained from the initial tableau .
Page 484
The slack for an activity is the difference between its latest finish time and its earliest fin- ish time . In symbols , Slack = LF - EF . ( Since LF - EF = LS - ES , either difference actually can be used to calculate slack . ) ...
The slack for an activity is the difference between its latest finish time and its earliest fin- ish time . In symbols , Slack = LF - EF . ( Since LF - EF = LS - ES , either difference actually can be used to calculate slack . ) ...
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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 |