Introduction to Operations ResearchMethodology; Fundamentals; Techniques: mathematical programming; Techniques: probalistic models;Techniques: advanced topics in mathematical programming. |
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Page 169
... solve this problem by the simplex method . ( b ) Use the two - phase method to solve this problem by the simplex method . 7. Consider the example introduced in Sec . 5.6.4 . ( a ) Use the Big M method to solve this problem by the ...
... solve this problem by the simplex method . ( b ) Use the two - phase method to solve this problem by the simplex method . 7. Consider the example introduced in Sec . 5.6.4 . ( a ) Use the Big M method to solve this problem by the ...
Page 275
... solve for y * and y * , merely select two values of x1 , say zero and one , and solve the resulting two simultaneous equations . Thus , 2 4y * - 3y * = 11 so that y = 6 / 11 and y for player II is ( y1 , Y2 , Y3 ) −2y * + 2y * 2 11 I ...
... solve for y * and y * , merely select two values of x1 , say zero and one , and solve the resulting two simultaneous equations . Thus , 2 4y * - 3y * = 11 so that y = 6 / 11 and y for player II is ( y1 , Y2 , Y3 ) −2y * + 2y * 2 11 I ...
Page 594
... solve numerically . ( b ) Solve the problem as formulated in Part ( a ) . 5. Consider the convex programming problem , subject to and maximize ( 4x + 6x2 x3 2x3 } , - x13x2 8 5x1 + 2x2 ≤ 14 - X10 , X2 ≥ 0 . ( a ) Treat this problem as ...
... solve numerically . ( b ) Solve the problem as formulated in Part ( a ) . 5. Consider the convex programming problem , subject to and maximize ( 4x + 6x2 x3 2x3 } , - x13x2 8 5x1 + 2x2 ≤ 14 - X10 , X2 ≥ 0 . ( a ) Treat this problem as ...
Contents
Introduction 32 | 3 |
Planning an Operations Research Study | 12 |
Probability Theory 223 | 77 |
Copyright | |
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allocation assigned assumed b₁ b₂ 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 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 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