Algorithms

Evolutionary Algorithms MCQs With Answers

Welcome to the Evolutionary Algorithms MCQs with Answers. In this post, we have shared Evolutionary Algorithms Online Test for different competitive exams. Find practice Evolutionary Algorithms Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Evolutionary Algorithms.

Evolutionary Algorithms Online Quiz

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  • Test Name: Evolutionary Algorithms MCQ Quiz Practice
  • Type: Quiz Test
  • Total Questions: 40
  • Total Marks: 40
  • Time: 40 minutes

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Evolutionary Algorithms MCQs

Evolutionary Algorithms

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1 / 40

What is the key difference between genetic algorithms and evolutionary strategies?

2 / 40

What is the primary goal of the fitness function in evolutionary algorithms?

3 / 40

Which evolutionary algorithm is based on the principles of Darwinian evolution?

4 / 40

Which evolutionary algorithm is inspired by the annealing process in metallurgy?

5 / 40

Which evolutionary algorithm is inspired by the social behavior of birds and fish?

6 / 40

What is the primary use of fitness scaling in genetic algorithms?

7 / 40

Which evolutionary algorithm concept is inspired by the behavior of social insects?

8 / 40

What is the main advantage of using particle swarm optimization?

9 / 40

What is the main purpose of the recombination operator in genetic algorithms?

10 / 40

What is the main goal of selection in genetic algorithms?

11 / 40

Which term describes the process of selecting the best individuals to reproduce in genetic algorithms?

12 / 40

Which algorithm is inspired by the foraging behavior of ants?

13 / 40

What is the main benefit of using tournament selection in genetic algorithms?

14 / 40

What is the main purpose of the fitness landscape in evolutionary algorithms?

15 / 40

What is the purpose of a fitness proportionate selection in genetic algorithms?

16 / 40

What is the primary goal of evolutionary strategies in optimization problems?

17 / 40

Which evolutionary algorithm concept involves evaluating the entire population at once?

18 / 40

Which term refers to a potential solution in a genetic algorithm?

19 / 40

What is the main purpose of crossover in genetic algorithms?

20 / 40

Which evolutionary algorithm is particularly useful for optimizing real-valued functions?

21 / 40

What is the primary goal of differential evolution algorithms?

22 / 40

Which operator in genetic algorithms is responsible for creating new offspring?

23 / 40

Which term refers to the adjustment of gene values within a chromosome in genetic algorithms?

24 / 40

Which term describes the process of combining two parent chromosomes to create offspring?

25 / 40

Which operator in genetic algorithms introduces diversity by randomly altering genes?

26 / 40

What is the key advantage of using elitism in genetic algorithms?

27 / 40

Which evolutionary algorithm is inspired by the behavior of swarms?

28 / 40

What is the purpose of the roulette wheel selection method in genetic algorithms?

29 / 40

Which term describes the complete set of solutions being considered in an evolutionary algorithm?

30 / 40

Which term refers to a single variable within a chromosome in genetic algorithms?

31 / 40

Which evolutionary algorithm concept involves individuals being replaced one at a time?

32 / 40

Which evolutionary algorithm concept involves individuals migrating between subpopulations?

33 / 40

What is the main purpose of the mutation operator in genetic algorithms?

34 / 40

What is the main characteristic of evolutionary programming?

35 / 40

Which operator in genetic algorithms helps to prevent the population from becoming too similar?

36 / 40

What is the main advantage of using evolutionary algorithms?

37 / 40

What is the main characteristic of a generational model in genetic algorithms?

38 / 40

What is the role of elitism in genetic algorithms?

39 / 40

What is a fitness function in the context of evolutionary algorithms?

40 / 40

Which evolutionary algorithm concept is inspired by natural selection?

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