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7 D 10 15 14 5 80 2 17 Co 8 03 00 B 9 11 E 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 the Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. 1. Encode the problem and create an initial population of 4 different chromosomes. 2. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. 3. 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. 4. Would the usual method of mutation work here? Explain your opinion.

7 D 10 15 14 5 80 2 17 Co 8 03 00 B 9 11 E 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 the Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. 1. Encode the problem and create an initial population of 4 different chromosomes. 2. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. 3. 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. 4. Would the usual method of mutation work here? Explain your opinion.

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Please use Genetic Algorithm to solve the problem

 

7 D 10 15 14 5 80 2 17 Co 8 03 00 B 9 11 E
Transcribed Image Text:7 D 10 15 14 5 80 2 17 Co 8 03 00 B 9 11 E
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 the Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. 1. Encode the problem and create an initial population of 4 different chromosomes. 2. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. 3. 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. 4. Would the usual method of mutation work here? Explain your opinion.
Transcribed Image Text: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 the Genetic Algorithm. You can start at any point and end at any point but keep in mind that every city must be visited. 1. Encode the problem and create an initial population of 4 different chromosomes. 2. Using an appropriate fitness function, perform natural selection to choose the 2 fittest chromosomes. 3. 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. 4. Would the usual method of mutation work here? Explain your opinion.
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