[Solved]Question 7 Use Genetic Algorithm Described Example 51 Page 134 Study Guide Solve Following Q37197688

Question 7 (a) Use the genetic algorithm described in Example 5.1 on page 134 of the study guide to solve the following optimisation problem: Maximise: 340z 10zor Ps 31 Perform one iteration of the algorithm with the following four strings as the original population: String 1: 11011. String 2: 01010, String 3: 01000, String 4: 10101 Of course, we cannot use actual roulette wheel selection in the assignment, so make the following assumptions (where, as in the study guide, string positions are counted from the left): (1) Selection. Suppose that roulette wheel selection gave strings 1 and 2 as a breeding pair, and strings 2 and 4 as a breeding pair (2) Crossover For the breeding pair string 1, string 2 the crossover position 3 was randomly selected, and for the breeding pair string 2 and string 4 the crossover position 4 was randomly selected. (3) Mutation. All the children had mutation position 2. Give the fitness table (i.e. Table 5.1), and the fitness and probability to be selected table in your answer (Table 5.2). Also give the fitness of the new population table. (Table 5.4) (b) Suppose that a genetic algorithm is used to find a solution to a 9-city travelling salesman problem and the following strings have been selected as parents: Parent 1: (4 96318257) Parent 2: (612759834) In each of the following cases give the two offspring that are generated: (i) A partially mapped crossover operator (PMX) is used with crossover between positions 2 and 3 and positions 6 and 7 (ii) The C1 crossover operator is used with crossover between positions 6 and 7. (iii) The crossover template 110100011 is used. Show transcribed image text Question 7 (a) Use the genetic algorithm described in Example 5.1 on page 134 of the study guide to solve the following optimisation problem: Maximise: 340z 10zor Ps 31 Perform one iteration of the algorithm with the following four strings as the original population: String 1: 11011. String 2: 01010, String 3: 01000, String 4: 10101 Of course, we cannot use actual roulette wheel selection in the assignment, so make the following assumptions (where, as in the study guide, string positions are counted from the left): (1) Selection. Suppose that roulette wheel selection gave strings 1 and 2 as a breeding pair, and strings 2 and 4 as a breeding pair (2) Crossover For the breeding pair string 1, string 2 the crossover position 3 was randomly selected, and for the breeding pair string 2 and string 4 the crossover position 4 was randomly selected. (3) Mutation. All the children had mutation position 2. Give the fitness table (i.e. Table 5.1), and the fitness and probability to be selected table in your answer (Table 5.2). Also give the fitness of the new population table. (Table 5.4) (b) Suppose that a genetic algorithm is used to find a solution to a 9-city travelling salesman problem and the following strings have been selected as parents: Parent 1: (4 96318257) Parent 2: (612759834) In each of the following cases give the two offspring that are generated: (i) A partially mapped crossover operator (PMX) is used with crossover between positions 2 and 3 and positions 6 and 7 (ii) The C1 crossover operator is used with crossover between positions 6 and 7. (iii) The crossover template 110100011 is used.

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Answer to Question 7 (a) Use the genetic algorithm described in Example 5.1 on page 134 of the study guide to solve the following … . . .