NPTEL Introduction To Soft Computing Week 5 Assignment Answers 2025
1. Which of the following is a well-known crossover technique used in real-coded Genetic
Algorithms (GAs)?
a. Linear crossover
b. Blend crossover
c. Binary simulated crossover
d. All of the above
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2. Which of the following is a characteristic of the Blend Crossover technique in real-coded
Genetic Algorithms (GAs)?
a. The child inherits genes that are random selections from the parents
b. The child is generated by linearly interpolating between the genes of two parents
c. The child’s genes are randomly swapped between parents
d. It maintains a constant gene value throughout the crossover process
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3. Which of the following is a limitation of crossover techniques in real-coded Genetic
Algorithms (GAs)?|
a. They always lead to the global optimal solution.
b. They are independent of the chromosome length.
c. If parameters are not chosen correctly, they may lead to premature convergence.
d. They are computationally cheaper than other methods like binary crossover.
Answer :-
4. Binary crossover techniques are applicable to Order Coded Genetic Algorithms (GAs).?
a. False
b. True
Answer :-
5. What is a key characteristic of real-coded crossover techniques that makes them incompatible with Order-coded Genetic Algorithms (GAs)?
a. They generate real-valued offspring, which could disrupt the gene order in order- coded chromosomes.
b. They are slower than binary crossover techniques.
c. They only work with binary-encoded chromosomes.
d. They only apply to problems with continuous variables, not discrete ones.
Answer :-
6. Given two parent solutions represented as real-valued chromosomes:
Parent 1: P1=[(2.5,4.8,3.2,6.0]
Parent 2: P2=[1.0,5.5,2.0,4.5]
Perform a Single-point order crossover at the second position (crossover point) to generate
two offspring solutions.
What are the offspring solutions?
a. C1=[2.5,5.5,2.0,4.5] ,C2=[1.0,4.8,3.2,6.0]
b. C1=[2.5,4.8,3.2,6.0] ,C2=[1.0,5.5,2.0,4.5]
c. C1=(2.5,5.5,3.2,6.0] ,C2=[1.0,4.8,2.0,4.5]
d. C1=[2.5,4.8,2.0,6.0], C2=[1.0,5.5,3.2,4.5]
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7.
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8. Why is fitness sealing used in Genetic Algorithms ?
a. To increase the mutation rate and introduce more randomness in the search process.
b. To adjust raw fitness values so that the Genetic Algorithm can differentiate between the best and worst individuals.
c. To ensure that crossover and mutation always produce optimal solutions.
d. To eliminate local optima and guarantee convergence to the global optimum.
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9. What is the primary challenge in solving a MOOP (Multi-Objective Optimization Problem)?
a. Finding a single global optimal solution.
b. Managing multiple objectives that often conflict with each other.
c. Reducing the computational complexity of the problem.
d. Ensuring convergence within a limited number of iteration
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10. Which of the following statements about Pareto optimal solutions is TRUE?
a. They represent a single optimal solution for all objectives.
b. They are irrelevant in problems with non-conflicting objectives.
c. They consist of solutions where improving one objective compromises another.
d. They simplify the optimization process by eliminating conflicting objectives.
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