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 573
... programming problem . Maximize subject to and x2 + x2 ≤ 4 Z = 2x1 + x2 , X2 ≥ 0 . Use dynamic programming to solve this problem . 11.3-18 . Consider the following nonlinear programming problem . and CHAPTER 11 PROBLEMS 573.
... programming problem . Maximize subject to and x2 + x2 ≤ 4 Z = 2x1 + x2 , X2 ≥ 0 . Use dynamic programming to solve this problem . 11.3-18 . Consider the following nonlinear programming problem . and CHAPTER 11 PROBLEMS 573.
Page 574
... programming problem . and 12 Integer Programming In Chap . 3 you saw several. Minimize subject to x2 + x2 ≥ 2 . Z = x2 + 2x2 ( There are no nonnegativity constraints . ) Use dynamic program- ming to solve this problem . 11.3-19 ...
... programming problem . and 12 Integer Programming In Chap . 3 you saw several. Minimize subject to x2 + x2 ≥ 2 . Z = x2 + 2x2 ( There are no nonnegativity constraints . ) Use dynamic program- ming to solve this problem . 11.3-19 ...
Page 709
... programming problem : Maximize subject to and x2 + x ≤ 1 f ( x ) = x1 + x2 , X2 ≥ 0 . ( a ) Verify that this is a convex programming problem . ( b ) Solve this problem graphically . 13.2-10 . Consider the following nonlinear ...
... programming problem : Maximize subject to and x2 + x ≤ 1 f ( x ) = x1 + x2 , X2 ≥ 0 . ( a ) Verify that this is a convex programming problem . ( b ) Solve this problem graphically . 13.2-10 . Consider the following nonlinear ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost CPF solution CPLEX decision variables described dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphical identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ 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 |