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. |
From inside the book
Results 1-3 of 86
Page 192
... equations refer to the constraint boundary equations that yield ( define ) the indicated CPF solution . For any linear programming problem with n decision variables , each CPF solution lies at the intersection of n constraint boundaries ...
... equations refer to the constraint boundary equations that yield ( define ) the indicated CPF solution . For any linear programming problem with n decision variables , each CPF solution lies at the intersection of n constraint boundaries ...
Page 199
... equations , which we called its defining equations . The key ques- tion is : How do we tell whether a particular constraint boundary equation is one of the defining equations when the problem is in augmented form ? The answer ...
... equations , which we called its defining equations . The key ques- tion is : How do we tell whether a particular constraint boundary equation is one of the defining equations when the problem is in augmented form ? The answer ...
Page 850
... equation expressing this principle is called the balance equation for state n . Af- ter constructing the balance equations for all the states in terms of the unknown P , prob- abilities , we can solve this system of equations ( plus an ...
... equation expressing this principle is called the balance equation for state n . Af- ter constructing the balance equations for all the states in terms of the unknown P , prob- abilities , we can solve this system of equations ( plus an ...
Other editions - View all
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 Courseware CPLEX decision variables described dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given graphical identify increase initial BF solution integer 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 resource right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ 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 |