Introduction to Operations ResearchMethodology; Fundamentals; Techniques: mathematical programming; Techniques: probalistic models;Techniques: advanced topics in mathematical programming. |
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Page 244
... optimal policy for the remaining stages is independent of the policy adopted in previous stages . Given the state in which the salesman is currently located , the optimal life insurance policy ( and its associated route ) from this ...
... optimal policy for the remaining stages is independent of the policy adopted in previous stages . Given the state in which the salesman is currently located , the optimal life insurance policy ( and its associated route ) from this ...
Page 364
... optimal . This characterization of optimal policies can be used to determine which policies are not optimal , but it cannot be used to find the optimal policy . Of course , one method for solving the optimization problem is to enumerate ...
... optimal . This characterization of optimal policies can be used to determine which policies are not optimal , but it cannot be used to find the optimal policy . Of course , one method for solving the optimization problem is to enumerate ...
Page 368
... optimal policy . As a simple example , suppose there are two batteries in a stockpile of ages S1 and S2 ( S2 > S1 ... policy is a LIFO ( last in , first out ) policy , whereas the latter is a FIFO ( first in , first out ) policy . The ...
... optimal policy . As a simple example , suppose there are two batteries in a stockpile of ages S1 and S2 ( S2 > S1 ... policy is a LIFO ( last in , first out ) policy , whereas the latter is a FIFO ( first in , first out ) policy . The ...
Contents
Introduction 32 | 3 |
Planning an Operations Research Study | 12 |
Probability Theory 223 | 23 |
Copyright | |
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allocation assigned assumed b₁ basic feasible solution basic solution 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 interval 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