2. Apply the first phase of the 2-phase simplex algorithm to the following linear pro-gramme giving the initial tableau and each further tableau produced. Give thestarting tableau for the second phase if there is one.maximize 2x1 x23x3subject toX2- x3 ≤ 2,x13x2+2x3 ≥ 3,2x12x2 x3 = 4,x1, x2, x3 0.

Please refer below pages.If you have any doubts please feel free to ask.Explanation:Step 1: Step 2:…

Answered: 2. Apply the first phase of the 2-phase…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Solve using the simplex algorithm.Maximize: 5x1 + 6x2Subject to: x1 + 2x2 ≤ 83x1 + 2x2 ≤ 12x1, x2 ≥ 0
Example For alternative optimal solut Min - 3 + x2 5. غلول x₁ + 2x₂ K 4 - + 2 ۲۱ لا بلا 012x6
IN OCTAVE Use Jacobi's algorithm to solve the following system of equations witha tolerance es =5%
Exercise 5.2 - please solve this pure integer programming model step by step using branch and bound : Max Z = -3x1 + 5x2 bounds : 5x1 - 7x2 >= 3 x1 <= 3 x2 <= 3 x1,x2 >= 0 and integer
:How finite difference and collocation methods are useful to solve BVPs. Also discuss stability of each method .
Please solve as soon as possible
Find the Ualue of x 2axt2 + 2 X+3
+ 7. Consider the feasible region shown below. Assume the origin (A) is feasible and the constraints are all constraints and the variables are all nonnegative. Suppose you wish to maximize 1 + over this feasible region and you are currently at point G. Which variable should enter the basis in the first iteration of the simplex algorithm if we wish to maximize the objective function improvement after the first iteration? O only 2₂ only Ⓒ* only A 1.₂. or s 1 H B G A: (0,0,0) B: (1,0,0) C (0, 1, 0) D: (0, 0, 1)
You, Alice and Bob are engineering a solution the Really Hard Problem and have come up with ten algorithmic solutions. Alice has analysed the code and expressed the run times of the ten solutions with the following ten functions: •fo(n) = (3n+3)³ • fi(n) = [₁2² f2(n) = n². (22+75) • f3(n) = 3log, n • f4(n) = fs(n) = log₂ (n^²) • fe(n) = log₂ (n² +5n-3) • fr(n) = log₂ (log₂ n+3) f8(n) = 2 f9(n) = 2222 a) Alice has asked you to help her classify these functions based on their asymptotic growth rate. That is, she wants you to prove a tight big-Theta bound for each function by following these steps. i. Use algebra to simply the function for ease of analysis. Remember the goal of simplification is to isolate terms and identify the dominant term. For instance, we might want to expand (n + 1)² to n² +2n+ 1 to see that n² is the dominant term. ii. Use your intuition, the limit test, or algebra to come up with a good guess of a tight bound. For instance, after isolating n² as the dominant term…
At Long John Silver’s (LJS), Platter 1 comes with 2 pieces of fish, 3 pieces of chicken, and 5 fried shrimp, while Platter 2 comes with 3 pieces of fish, 1 piece of chicken, and 8 fried shrimp. Platter 1 sells for 8 dollars and platter 2 sells for 10 dollars. If LJS has access to 1000 pieces of fish, 1200 pieces of chicken, and 2600 fried shrimp, what is the optimal number of platters LJS should make in order to maximize its profit? Note that the constraints relate to (please use these in order) fish, chicken, and shrimp. Note that problem 7 had three constraints (excluding the non-negativity constraints), and setting two pairs of those constraints to equality led to two extreme points on the feasible region. What INFEASIBLE point was at the intersection of the other pair of constraints? In the optimal solution to problem 7, the optimum was found at the intersection of two of the constraints that were not non-negativity constraints. Call these “binding” constraints. One of those…

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