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 156
3.3 , we pointed out that the values used for the model parameters ( the aij , bi , and c ; identified in Table 3.3 ) generally are just estimates of quantities whose true values will not become known until the linear programming study ...
3.3 , we pointed out that the values used for the model parameters ( the aij , bi , and c ; identified in Table 3.3 ) generally are just estimates of quantities whose true values will not become known until the linear programming study ...
Page 255
existent , so that the parameters in the original formulation may represent little more than quick rules of thumb provided by harassed line personnel . The data may even represent deliberate overestimates or underestimates to protect ...
existent , so that the parameters in the original formulation may represent little more than quick rules of thumb provided by harassed line personnel . The data may even represent deliberate overestimates or underestimates to protect ...
Page 284
Because e 1 is the maximum realistic value of , this indicates that cy and c2 together are insensitive parameters with respect to the Variation 2 model in Table 6.21 . There is no need to try to estimate these parameters more closely ...
Because e 1 is the maximum realistic value of , this indicates that cy and c2 together are insensitive parameters with respect to the Variation 2 model in Table 6.21 . There is no need to try to estimate these parameters more closely ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
SUPPLEMENT TO CHAPTER | 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 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
Bibliographic information
| Title | Introduction to Operations Research McGraw-Hill International Editions 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 | Pennsylvania State University |
| Digitized | 26 Aug 2009 |
| ISBN | 0071181636, 9780071181631 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |