Operations Research: An Introduction |
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Page 174
... yields exactly the same optimal solution vector X as in the first iteration . Since the corresponding extreme points have been considered previously , the first subproblem yields no new information at this point . [ Actually , p1 = 0 ...
... yields exactly the same optimal solution vector X as in the first iteration . Since the corresponding extreme points have been considered previously , the first subproblem yields no new information at this point . [ Actually , p1 = 0 ...
Page 337
... yields a2 . But intuitively one is tempted to choose a , since there is a chance that if 0 = 02 only $ 90 will be lost , while it is certain that a2 will yield a loss of $ 10,000 whether 0 = 01 01 or 02 . The Savage criterion ...
... yields a2 . But intuitively one is tempted to choose a , since there is a chance that if 0 = 02 only $ 90 will be lost , while it is certain that a2 will yield a loss of $ 10,000 whether 0 = 01 01 or 02 . The Savage criterion ...
Page 338
... yielding max 。, max ,, { v ( a1 , 0 , ) } . ( It is assumed that v ( a1 , 0 , ) repre- sents gain or profit . ) Similarly ... yields min { a min v ( a1 , 01 ) + ( 1 − a ) max v ( a1 , 01 ) } ai 01 - მკ The parameter a is known as the ...
... yielding max 。, max ,, { v ( a1 , 0 , ) } . ( It is assumed that v ( a1 , 0 , ) repre- sents gain or profit . ) Similarly ... yields min { a min v ( a1 , 01 ) + ( 1 − a ) max v ( a1 , 01 ) } ai 01 - მკ The parameter a is known as the ...
Contents
Basics of Operations Research | 1 |
PART | 13 |
The Simplex Method | 42 |
Copyright | |
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activities algorithm amount applied approximate arrival associated assumed basic becomes called changes Chapter coefficients column complete computations Consider constant constraints continuous corresponding cost criterion critical customers decision defined demand derivatives determined developed distribution dual effect elements equal equations equivalent event Example expected expression extreme feasible Figure Find formula function given gives hence illustrate increase independent indicated integer inventory iteration limit linear programming machine matrix maximize maximum mean minimize necessary Notice objective function obtained occurs operation optimal optimal solution optimum period Poisson possible presented probability problem procedure production queueing remaining represents respectively result S₁ satisfied schedule selected shown shows simplex method simulation situation solution Solve stage starting Suppose Table tableau unit variables waiting x₁ y₁ yields zero