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Download JNTUA M.Tech 1st Sem 2016 Feb Reg-Supple 9D04201 Advanced Optimization Techniques Question Paper

Download JNTUA (JNTU Anantapur) M.Tech ( Master of Technology) 1st Semester 2016 Feb Reg-Supple 9D04201 Advanced Optimization Techniques Previous Question Paper

This post was last modified on 30 July 2020

This download link is referred from the post: JNTUA M.Tech 1st Sem last 10 year 2010-2020 Previous Question Papers (JNTU Anantapur)


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Code: 9D04201

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M.Tech I Semester Regular & Supplementary Examinations February 2016

ADVANCED OPTIMIZATION TECHNIQUES

(Common to PE & PEED)

(For students admitted in 2013, 2014 & 2015 only)

Time: 3 hours

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Max Marks: 60

Answer any FIVE questions

All questions carry equal marks


  1. Find the optimum solution of the following function using (Big-M or 2-phase) simplex method.
    Minimize f = 9x1 + 2x2 + 3x3

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    Subject to
    -2x1 - x2 + 3x3 ≤ -5
    x1 - 2x2 + 2x3 ≥ -2
    x1, x2, x3 ≥ 0
  2. A salesman stationed at city A has to decide his tour plan to visit cities B, C, D, E and back to city A.

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    He should choose his path so that the total distance traveled is minimum. No sub touring is permitted.
    The distance between cities in kilometers is given below:
    Cities A B C D E
    A - 16 18 13 20
    B 16 - 21 27 14
    C 18 21 - 15 21
    D 13 27 15 - 19
    E 20 14 21 19 -
  3. (a) What are Kuhn-Tucker conditions? What are the necessary conditions of optimality as per Kuhn-Tucker conditions?
    (b) Use the Lagrange multiplier method to solve the following non-linear programming problem.

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    f(x) = 2x1 + x2 + 3x3 + 10x1 - 10x2 + 8x2 + 6x3 - 100
    Such that x1 + x2 + x3 = 20
    x1, x2, x3 ≥ 0
  4. Explain various genetic operators.
  5. (a) For the given function, complete two iterations of the steepest descent method starting from the given starting design point of (3, 1).

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    f(x1, x2) = 25x1² + 20x2 – 2x1 - x2
    (b) Consider the following two strings denoting the vectors X₁ and X₂:
    X₁ = {1 0 0 0 1 0 1 1 0 1}; X₂ = {0 1 1 1 1 1 0 1 1 0};
    Find the result of crossover at location 2.
  6. (a) What are the steps involved in solving problems using genetic programming?

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    (b) How does Genetic programming differ from genetic algorithms?
  7. (a) What is Pareto-optimality? Explain the basic terminology in Pareto-optimality.
    (b) What are the various techniques used for solving multi-objective problems?
  8. Explain the steps involved in the optimization of path synthesis of a four-bar mechanism.

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This download link is referred from the post: JNTUA M.Tech 1st Sem last 10 year 2010-2020 Previous Question Papers (JNTU Anantapur)

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