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 333
An upper , one - sided goal sets an upper limit that we do not want to exceed ( but falling under the limit is fine ) . 3. A two - sided goal sets a specific target that we do not want to miss on either side . Goal programming problems ...
An upper , one - sided goal sets an upper limit that we do not want to exceed ( but falling under the limit is fine ) . 3. A two - sided goal sets a specific target that we do not want to miss on either side . Goal programming problems ...
Page 345
One of management's goals in a goal programming problem is expressed algebraically as 3x + 4x2 + 2x3 = 60 , = where 60 is the specific numeric goal and the left - hand side gives the level achieved toward meeting this goal .
One of management's goals in a goal programming problem is expressed algebraically as 3x + 4x2 + 2x3 = 60 , = where 60 is the specific numeric goal and the left - hand side gives the level achieved toward meeting this goal .
Page 346
C ( b ) Management is wondering what would happen if the total profit goal were to be increased to wanting at least $ 140 million ( without any change in the original penalty weights ) . Solve the revised model with this change .
C ( b ) Management is wondering what would happen if the total profit goal were to be increased to wanting at least $ 140 million ( without any change in the original penalty weights ) . Solve the revised model with this change .
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activity additional algorithm allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution decision variables demand described determine direction distribution dual problem entering equal equations estimates example feasible feasible region 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 shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit weeks Wyndor Glass 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, Mark S. Hillier |
| Compiled by | Karl Schmedders, Mark S. Hillier |
| 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 |