Introduction to Operations ResearchMethodology; Fundamentals; Techniques: mathematical programming; Techniques: probalistic models;Techniques: advanced topics in mathematical programming. |
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Page 180
... tion is actually a weighted average of two basic feasible solutions . Geomet- rically , the solution must lie on the segment between two extreme points . To motivate the reason for this , consider a general linear programming model such ...
... tion is actually a weighted average of two basic feasible solutions . Geomet- rically , the solution must lie on the segment between two extreme points . To motivate the reason for this , consider a general linear programming model such ...
Page 519
... tion of the revised simplex method are left to the reader as an exercise.102 It would now be useful to summarize the advantages of the revised simplex method over the original simplex method . One is that the number of arithmetic ...
... tion of the revised simplex method are left to the reader as an exercise.102 It would now be useful to summarize the advantages of the revised simplex method over the original simplex method . One is that the number of arithmetic ...
Page 619
... tion , which proceeds as follows . To begin , eliminate the first variable from all but one ( say , the first ) of the equations by adding an appropriate mul- tiple of this equation to each of the others . ( For convenience , this one ...
... tion , which proceeds as follows . To begin , eliminate the first variable from all but one ( say , the first ) of the equations by adding an appropriate mul- tiple of this equation to each of the others . ( For convenience , this one ...
Contents
Introduction 3 2 | 3 |
Planning an Operations Research Study | 12 |
Probability Theory 223 | 77 |
Copyright | |
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allocation assigned assumed b₁ b₂ basic feasible solution c₁ calling units coefficient concave function Consider constraints convex convex function convex set corresponding decision variables decision-maker demand denote density function discrete random variable dual problem entering basic variable estimate event example expected value exponential distribution formulation given Hence illustrate integer inventory iteration leaving basic variable linear programming problem Markov chain mathematical matrix maximize minimize mixed strategy node non-basic variables non-negative normal distribution objective function obtained operations research optimal policy optimal solution optimal value original parameter payoff period player Poisson input possible primal problem probability distribution queueing model queueing system queueing theory random numbers sample space selected server service facility set of equations simplex method simulation slack variables solution procedure solve steady-state Suppose technique Theorem tion total cost variance waiting x₁ zero