## Introduction to the techniques of operations researchDept. of Industrial Engineering, Stanford University, 1966 - Business & Economics |

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### Contents

Chapter k Probability Theory | 1 |

Chapter 5 Statistical Inference and Decision Theory Chapter 6 Linear Programming | 1 |

Advanced Topics in Mathematical Programming | 1 |

Copyright | |

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### Common terms and phrases

allocation assigned assumed average basic feasible solution basic solution birth-death process bivariate random variable calling units coefficients column consider constraints continuous random variable corresponding decision variables demand denote density function discrete random variable dual problem dual simplex method dynamic programming entering basic variable Erlang distribution estimate event example expected value exponential distribution exponential service Figure finite flow capacity formulation Furthermore given Hence illustrate independent initial basic feasible integer inventory iteration leaving basic variable linear programming problem matrix Maximize mean service rate minimize node non-basic variables non-negative normal distribution objective function obtained optimal policy optimal solution parameters period Poisson input primal problem probability distribution production queueing model queueing system queueing theory random numbers restrictions sample space Section selected server service facility set of equations simulation slack variables solution procedure solved steady-state Suppose Theorem tion total cost variance yields