Inventory-production Theory: A Linear Policy Approach |
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Page 58
... distribution functions F + 1 ( x ) and Fo¡ ( x ) of x ° ; k and k + 1 Xk respectively , Fx + 1 ( x ) = 9 FX x + z yo ... function of x . Generally , integral equation ( 3.83 ) cannot be solved analytically . However , if y ° ( z ) is a ...
... distribution functions F + 1 ( x ) and Fo¡ ( x ) of x ° ; k and k + 1 Xk respectively , Fx + 1 ( x ) = 9 FX x + z yo ... function of x . Generally , integral equation ( 3.83 ) cannot be solved analytically . However , if y ° ( z ) is a ...
Page 59
... distribution function of x . Hence the Gram Charlier expansion is defined by ∞ FS ( x ) = Σ i C ; ( FS ) ( i ) N Φ ( x ) i = 0 i ! ( 3.84 ) where ON ( i ) is the i - th derivation of the standardized normal distribution function . For ...
... distribution function of x . Hence the Gram Charlier expansion is defined by ∞ FS ( x ) = Σ i C ; ( FS ) ( i ) N Φ ( x ) i = 0 i ! ( 3.84 ) where ON ( i ) is the i - th derivation of the standardized normal distribution function . For ...
Page 60
... distribution screwness and curtosis are of no great importance , the same holds a fortiori for the stationary distribution function of x . Hence F3 ( x ) ~ ( x ) would be a good approximation and , as our numerical results will show ...
... distribution screwness and curtosis are of no great importance , the same holds a fortiori for the stationary distribution function of x . Hence F3 ( x ) ~ ( x ) would be a good approximation and , as our numerical results will show ...
Contents
A linear Policy Approach | 1 |
P andor Q0 | 4 |
The linearquadratic model | 7 |
Copyright | |
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1+K₁ algorithm approximation ARMA-process assumption asymptotic balance equation calculated Chap chapter conditional means cost criterion cost deviations cost functions cost parameters costs are given defined demand sequence denotes derive deterministic distribution function dynamic certainty equivalents dynamic programming Ek+1 Êx+1 exponential smoothing follows forecasts Gauss-Markov Gauss-Markov process Gaussian Hence inventory costs inventory problem inventory-production investigate K₁ Kalman filter linear decision rule linear policy LNQ-approach non-quadratic Numerical Results obtains optimal costs optimal decision optimal policy period Piecewise Linear Costs Prob probability distribution procedure pure inventory quadratic quadratic functions R₁ random variables random walk recursive reduces respect restricted S,S)-policy safety stock Seiten sequence of demand set-up costs shown solved space representation stationary structure suboptimal Substituting variances white noise Wiener-Hopf equation xk+1 xx+1 z-transform ас Ик