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. |
From inside the book
Results 1-3 of 84
Page 9
Frequently , much of the needed data will not be available when the study begins , either because the information never has been kept or because what was kept is outdated or in the wrong form . Therefore , it often is necessary to ...
Frequently , much of the needed data will not be available when the study begins , either because the information never has been kept or because what was kept is outdated or in the wrong form . Therefore , it often is necessary to ...
Page 649
CASE 12.3 STOCKING SETS a Daniel Holbrook , an expeditor at the local warehouse for Furniture City , sighed as he moved boxes and boxes of inventory to the side in order to reach the shelf where the particular item he needed was located ...
CASE 12.3 STOCKING SETS a Daniel Holbrook , an expeditor at the local warehouse for Furniture City , sighed as he moved boxes and boxes of inventory to the side in order to reach the shelf where the particular item he needed was located ...
Page 984
Some coordination is needed between the inventories of any particular product at the different echelons . Since the inventory at each echelon ( except the top one ) is replenished from the next higher echelon , the inventory level ...
Some coordination is needed between the inventories of any particular product at the different echelons . Since the inventory at each echelon ( except the top one ) is replenished from the next higher echelon , the inventory level ...
What people are saying - Write a review
We haven't found any reviews in the usual places.
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 allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables 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 graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero