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 54
( Try it and see if you first obtain the following inappropriate choice of decision
variables . ) Because one set of decisions is the amount of each product grade to
produce , it would seem natural to define one set of decision variables
accordingly .
( Try it and see if you first obtain the following inappropriate choice of decision
variables . ) Because one set of decisions is the amount of each product grade to
produce , it would seem natural to define one set of decision variables
accordingly .
Page 75
With 10 plants , 10 machines , 10 products , and 10 months , this gives a total of
21 , 000 decision variables , as outlined below . Decision Variables . 10 , 000
production variables : one for each combination of a plant , machine , product ,
and ...
With 10 plants , 10 machines , 10 products , and 10 months , this gives a total of
21 , 000 decision variables , as outlined below . Decision Variables . 10 , 000
production variables : one for each combination of a plant , machine , product ,
and ...
Page 78
For each production capacity constraint , each term in the summation consists of
a decision variable ( the production ... value to the current inventory variable ,
given the values of all the other decision variables including the inventory level
for ...
For each production capacity constraint , each term in the summation consists of
a decision variable ( the production ... value to the current inventory variable ,
given the values of all the other decision variables including the inventory level
for ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
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Common terms and phrases
activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary calculations called capacity changes coefficients column complete Consider constraints construct corresponding cost CPF solution demand described determine direction distribution dual problem entering equal equations estimates example feasible FIGURE final flow problem Formulate 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 resource respective resulting revised Select shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero