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 289
Consider the two versions of the dual problem for the radiation therapy example that are given in Tables 6.15 and 6.16 . Review in Sec . 6.4 the general discussion of why these two versions are completely equivalent .
Consider the two versions of the dual problem for the radiation therapy example that are given in Tables 6.15 and 6.16 . Review in Sec . 6.4 the general discussion of why these two versions are completely equivalent .
Page 574
Consider the following nonlinear programming problem . Minimize Z = xy + 2x x 20 , X2 20 . Use dynamic programming to solve this problem . subject to x } + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic programming to ...
Consider the following nonlinear programming problem . Minimize Z = xy + 2x x 20 , X2 20 . Use dynamic programming to solve this problem . subject to x } + xż z 2 . ( There are no nonnegativity constraints . ) Use dynamic programming to ...
Page 709
Consider the following function : f ( x ) = 5x , + 2x3 + x3 – 3x3 / 4 + 4x + 2x + x3 + 3x3X6 + 6x2 + 3x6x2 + x ?. Show that f ( x ) is convex by expressing it as a sum of functions of one or two variables and then showing ( see Appendix ...
Consider the following function : f ( x ) = 5x , + 2x3 + x3 – 3x3 / 4 + 4x + 2x + x3 + 3x3X6 + 6x2 + 3x6x2 + x ?. Show that f ( x ) is convex by expressing it as a sum of functions of one or two variables and then showing ( see Appendix ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
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 |
| 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 |