Function optimization is when you find the optimum point of a function, either minimum or maximum. You will be creating Genetic Algorithm to find maximum point of this function: ƒ(x, y) = (l− x)²e¬x²−(y+1)² − (x−x³ − y³) e¯ −µ² where parameters x and y are between -2 and 2. Use a Genetic Algorithm with the population size of 8, the crossover propability of 0.7, and the mutation probability of 0.01. Use total number of generation as 200. Your code should find the (x,y) pair that gives the maximum point and its fitness value f(x,y).

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
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Function optimization is when you find the optimum point of a function, either minimum or maximum. You will be creating Genetic
Algorithm to find maximum point of this function:
f(x, y) = (1-x)²e=x²-(y+1)² -(x-x³-1³) e-x²-1²
where parameters x and y are between -2 and 2. Use a Genetic Algorithm with the population size of 8, the crossover propability of
0.7, and the mutation probability of 0.01. Use total number of generation as 200.
Your code should find the (x,y) pair that gives the maximum point and its fitness value f(x,y).
Transcribed Image Text:Function optimization is when you find the optimum point of a function, either minimum or maximum. You will be creating Genetic Algorithm to find maximum point of this function: f(x, y) = (1-x)²e=x²-(y+1)² -(x-x³-1³) e-x²-1² where parameters x and y are between -2 and 2. Use a Genetic Algorithm with the population size of 8, the crossover propability of 0.7, and the mutation probability of 0.01. Use total number of generation as 200. Your code should find the (x,y) pair that gives the maximum point and its fitness value f(x,y).
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