Introduction to Operations ResearchCD-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 , x1 + x3 = 4 . Given
this equation , xı 5 4 if and only if 4 - xy = x3 20. Therefore , the original constraint
x1 ...
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 , x1 + x3 = 4 . Given
this equation , xı 5 4 if and only if 4 - xy = x3 20. Therefore , the original constraint
x1 ...
Page 212
The insight involves the coefficients of the slack variables and the information
they give . It is a direct result of the initialization , where the ith slack variable Xnt ;
is given a coefficient of +1 in Eq . ( i ) and a coefficient of 0 in every other equation
...
The insight involves the coefficients of the slack variables and the information
they give . It is a direct result of the initialization , where the ith slack variable Xnt ;
is given a coefficient of +1 in Eq . ( i ) and a coefficient of 0 in every other equation
...
Page 484
This figure makes it easy to see how much slack each activity has . The slack for
an activity is the difference between its latest finish time and its earliest finish time
. In symbols , Slack LF – EF . ( Since LF – EF = LS - ES , either difference ...
This figure makes it easy to see how much slack each activity has . The slack for
an activity is the difference between its latest finish time and its earliest finish time
. In symbols , Slack LF – EF . ( Since LF – EF = LS - ES , either difference ...
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activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming Maximize million Minimize month needed node nonbasic variables objective function obtained operations optimal optimal solution original parameters path plant possible presented primal problem Prob procedure profit programming problem provides range remaining resource respective resulting revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero