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THE NATURE OF OPERATIONS
CHAPTER 3 NETWORK ANALYSIS
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algorithm analysis arrival assume assumptions basic feasible solution basic variable closed set coefficients column complementary consider constants constraint convex convex set corresponding cost cumulative distribution function decision variables defined demand denoted density function determine dynamic programming enter the basis equal equations event example exponential distribution formulation given Golden Section Search Hence increase initial integer program inventory linear programming problem machine Markov mathematical Maximize maximum Minimize negative exponential node nonbasic variable nonlinear programming nonnegative normal objective function obtained occur operations research optimal solution optimal value parameters Poisson Poisson process possible primal probability density function procedure profit quadratic programming queue random numbers random variable represents right-hand-side sequence server simplex method simulation language solve stage steady-state Step Subject Table tableau technique Theorem tion transition diagram unit variance vector zero