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Object Reward Weight A 20 1 B 5 2 C 10 3 D 40 8 E 15 7 FL 25 4 G 4 5 H 7 2 Maximum weight = 12 The above problem is a 0/1 Knapsack problem. You have to carry the different objects in your bag in a way such that the reward is maximized without exceeding the weight limit. You can carry an object exactly once but you always have to carry the object labeled "H". Assuming you are asked to use Genetic Algorithm for this problem, answer the following questions 1. Encode the problem and create an initial population of 4 different chromosomes 2. Explain what would be an appropriate fitness function for this problem. Use the fitness function and perform natural selection to choose the 2 fittest chromosomes. 3. Using the selected chromosomes perform a single-point crossover to get 2 offspring. 4. Perform mutation and check the fitness of the final offspring. Explain your work.

Object Reward Weight A 20 1 B 5 2 C 10 3 D 40 8 E 15 7 FL 25 4 G 4 5 H 7 2 Maximum weight = 12 The above problem is a 0/1 Knapsack problem. You have to carry the different objects in your bag in a way such that the reward is maximized without exceeding the weight limit. You can carry an object exactly once but you always have to carry the object labeled "H". Assuming you are asked to use Genetic Algorithm for this problem, answer the following questions 1. Encode the problem and create an initial population of 4 different chromosomes 2. Explain what would be an appropriate fitness function for this problem. Use the fitness function and perform natural selection to choose the 2 fittest chromosomes. 3. Using the selected chromosomes perform a single-point crossover to get 2 offspring. 4. Perform mutation and check the fitness of the final offspring. Explain your work.

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 provide a solution for the Knapsack Problem using Genetic Algorithm:

 

Object Reward Weight A 20 1 B 5 2 C 10 3 D 40 8 E 15 7 FL 25 4 G 4 5 H 7 2
Transcribed Image Text:Object Reward Weight A 20 1 B 5 2 C 10 3 D 40 8 E 15 7 FL 25 4 G 4 5 H 7 2
Maximum weight = 12 The above problem is a 0/1 Knapsack problem. You have to carry the different objects in your bag in a way such that the reward is maximized without exceeding the weight limit. You can carry an object exactly once but you always have to carry the object labeled "H". Assuming you are asked to use Genetic Algorithm for this problem, answer the following questions 1. Encode the problem and create an initial population of 4 different chromosomes 2. Explain what would be an appropriate fitness function for this problem. Use the fitness function and perform natural selection to choose the 2 fittest chromosomes. 3. Using the selected chromosomes perform a single-point crossover to get 2 offspring. 4. Perform mutation and check the fitness of the final offspring. Explain your work.
Transcribed Image Text:Maximum weight = 12 The above problem is a 0/1 Knapsack problem. You have to carry the different objects in your bag in a way such that the reward is maximized without exceeding the weight limit. You can carry an object exactly once but you always have to carry the object labeled "H". Assuming you are asked to use Genetic Algorithm for this problem, answer the following questions 1. Encode the problem and create an initial population of 4 different chromosomes 2. Explain what would be an appropriate fitness function for this problem. Use the fitness function and perform natural selection to choose the 2 fittest chromosomes. 3. Using the selected chromosomes perform a single-point crossover to get 2 offspring. 4. Perform mutation and check the fitness of the final offspring. Explain your work.
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