Please provide a solution for the Knapsack Problem using Genetic Algorithm: ObjectRewardWeightA201B52C103D408E157FL254G45H72 Maximum weight = 12The above problem is a 0/1 Knapsack problem. You have to carry the different objects in yourbag in a way such that the reward is maximized without exceeding the weight limit. You cancarry an object exactly once but you always have to carry the object labeled "H". Assuming youare asked to use Genetic Algorithm for this problem, answer the following questions1. Encode the problem and create an initial population of 4 different chromosomes2. Explain what would be an appropriate fitness function for this problem. Use the fitnessfunction 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.

1. Encoding the problem and creating an initial populationIn a 0/1 Knapsack problem with a genetic…

Answered: Object Reward Weight A 20 1 B 5 2 C 10…

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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Code this In python 13. Describe and analyze an algorithm to determine the number of shortest paths from a source vertex s to a target vertex t in an arbitrary directed graph G with weighted edges. You may assume that all edge weights are positive and that all necessary arithmetic operations can be performed in Exercises 0(1) time. [Hint: Compute shortest path distances from s to every other vertex. Throw away all edges that cannot be part of a shortest path from s to another vertex. What's left?]
Find the best solution for the 0-1 knapsack problem using backtracking algorithm. We have 5 items with price and weight: $50 $30 $40 $100 $20 10 1. 2. 3. 2 4. 10 5. 5 Limitation on the weight is: W = 21
Using Python
Find the best solution for the 0-1 knapsack problem using backtracking algorithm. We have 5 items with price and weight: $50 $30 $40 $100 $20 10 1. 2. 3. 2 4. 10 5. 5 Limitation on the weight is: W = 21
Game of 8 queens.Algorithmic solutions to the problems must be generated, with each of the following algorithm design techniques, in the Python language. Greedy Algorithms, Dynamic Programming, Bactracking, Branch and Bound.Calculate and analyze the complexity t(n) of each algorithm.Perform average comparison (minimum 3 executions with the same data pool) of time and memory consumption for each technique and algorithm.Given a chess board of size nxn, find the way(s) to place n queens, without any of them threatening each other.
4- Given the following graph, apply greedy algorithm to move from 0 to 4. 8 7 1 4 2 4 14 8 11 4 10 1 6. 5 clas TW 1 ra 3. 2.
There are many applications of Shortest Path Algorithm. Consider the problem of solving a jumbled Rubik's Cube in the fewest number of moves. I claim that this problem can be solved using a Shortest Path Algorithm. Determine whether this statement is TRUE or FALSE. NOTE: if you want to check if this statement is TRUE, think about how the Rubik's Cube Problem can be represented as a graph. What are the vertices? Which pairs of vertices are connected with edges? What is your source vertex and what is your destination vertex? How would Dijkstra's Algorithm enable you to find the optimal sequence of moves to solve a jumbled cube in the fewest number of moves?
Devise an efficient algorithm for finding the second largest element in a sequence of nelements and determine the worst case complexity of your algorithm. Please explain clearly"determine the worst - case complexity of your algorithm." Thank you so much.
How does dynamic programming differ from greedy algorithms in algorithm design?
in theatheory of algorithms , what does NP stands for ?
Please in python
Cliques The Clique problem is finding the subsets of vertices all adjacent to each other. The maximum clique is the largest complete subgraph with every vertex connected by an edge. Cliques are studied in social networks, bioinformatics, and computational chemistry. Describe the brute force algorithm to find the maximum clique. What algorithm complexity class is the brute force solution to the clique problem? What time complexity is the brute force algorithm to find the maximum clique? How does the graph of a clique differ from the graph of a social network influencer? List the number of algorithm steps for graphs with the following vertex count: 10,100,1000

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