## 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 452

Use the alto be a shortest - path problem ? gorithm

Use the alto be a shortest - path problem ? gorithm

**described**in Sec . 9.4 to find the minimum spanning tree ( b ) Use the algorithm**described**in Sec . 9.3 to solve this shortest- for each of these networks . path problem . c ( c ) ...Page 740

14.5-5 and its hint ) that this linear programming problem and the one given for player 1 are dual to each other in the sense

14.5-5 and its hint ) that this linear programming problem and the one given for player 1 are dual to each other in the sense

**described**in Secs . 6.1 and 6.4 . This fact has several important implications . One implication is that the ...Page 838

The only essential requirement for queueing theory to be applicable is that changes in the number of customers waiting for a given service occur just as though the physical situation

The only essential requirement for queueing theory to be applicable is that changes in the number of customers waiting for a given service occur just as though the physical situation

**described**in Fig . 17.2 ( or a legitimate counterpart ) ...### What people are saying - Write a review

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### Other editions - View all

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