G E N E T I C - A L G O R I T H M This is a map of 7 cities (A, B, C, D, E, F, and G) that are connected with each other via different paths. Your job is to visit every city just once covering the minimum distance possible. You have to find the optimal combination of cities using a Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. Encode the problem and create an initial population of 4 different chromosomes. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. Perform single-point crossover from the 3rd index of your selected chromosomes to get 2 offspring. Are they eligible as a solution? If not, explain with reason.
G E N E T I C - A L G O R I T H M This is a map of 7 cities (A, B, C, D, E, F, and G) that are connected with each other via different paths. Your job is to visit every city just once covering the minimum distance possible. You have to find the optimal combination of cities using a Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. Encode the problem and create an initial population of 4 different chromosomes. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. Perform single-point crossover from the 3rd index of your selected chromosomes to get 2 offspring. Are they eligible as a solution? If not, explain with reason.
Fundamentals of Information Systems
8th Edition
ISBN:9781305082168
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter7: Knowledge Management And Specialized Information Systems
Section: Chapter Questions
Problem 19SAT
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G E N E T I C - A L G O R I T H M
This is a map of 7 cities (A, B, C, D, E, F, and G) that are connected with each other via different paths. Your job is to visit every city just once covering the minimum distance possible. You have to find the optimal combination of cities using a Genetic
- Encode the problem and create an initial population of 4 different chromosomes.
- Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes.
- Perform single-point crossover from the 3rd index of your selected chromosomes to get 2 offspring. Are they eligible as a solution? If not, explain with reason.
- Would the usual method of mutation work here? Explain your opinion.
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B
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G
E
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2.
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