I need help with the genetic algorithm. Whenever i select the genetic algorithm, it always displays no solution. How do I fix this, below i provided all my classes for this and the problem description. Also, how do i make a method so the board prints

this is my program description:

CS$4200--$ Project $2$: N$-$Queen $($n $=8)$

Local search algorithms are very efficient in solving n$-$Queen problems. You are asked to implement the following two algorithms to solve the n$-$queen problem:

Time elapsed: $52$

$1)$ Straight$-$forward steepest$-$ascent hill climbing as described on page $9$ of our lecture "local search".

$2)$ Your choice of one of the following algorithms: simulated annealing search algorithm $($page $18$ of our $$local search$$ lecture$)$; the genetic algorithm $($page $26$ of our "local search" lecture$)$; or the MIN$-$CONFLICTS algorithm $($page $42$ of our $"$CSP$"$ lecture$).$

For analysis, you should generate a large number of n$-$queen instances $(>100)$ and solve them. Document the percentage of solved problems, search costs and the average running time. Explain why you get such results, for example, why the steepest$-$ascent hill climbing can only solve about $14\%$ of the problems, or what kind of improvements have you made to make your algorithms more efficient.

If you choose to implement the genetic algorithm, then your goal is to be able to solve the problem. You need to show that your program is able to solve at least three cases. You will also get $+10$ bonus points for solving the problem using genetic algorithm.

below is my code for genetic.java:

import java.util.Comparator;

import java.util.PriorityQueue;

import java.util.Random;

public class Genetic $\{$

public static void solveGenetic$($int population, int generations, double mutationRate$)\{$

Comparator QueenBoardComparator $=$ new QueenBoardComparator$()$;

PriorityQueue queue $=$ new PriorityQueue QueenBoardComparator$)$;

$//$ fill population with random boards

for $($int i $=0$; i $$ population; i$++)\{$

int$[]$ randomLayout $=$ QueenBoard.getRandomLayout$()$;

QueenBoard organism $=$ new QueenBoard$($randomLayout$)$;

queue.offer$($organism$)$;

$\}$

$//$ parent population is half the population

int parentPopulation $=$ population $/2$;

PriorityQueue parents $=$ new PriorityQueue QueenBoardComparator$)$;

$//$ for each generation, check if there is a solution, otherwise start breeding

for $($int g $=1$; g generations; g$++)\{$

$//$System$.$out.println$("$Starting generation $"+$ g$)$;

if $($queue$.$peek$().$getCrosses$()==0)\{$

System.out.println$("$Solution found! $"+$ queue.peek$().$toString$()+"$ with $"+$ queue.peek$().$getCrosses$()+"$ crosses."$)$;

return;

$\}$

$//$ for each generation, get the best organisms as parents

for $($int p $=0$; p $$ parentPopulation; p$++)\{$

parents.offer$($queue$.$poll$())$;

$\}$

$//$ now mate them

PriorityQueue children $=$ new PriorityQueue QueenBoardComparator$)$;

for $($int m $=0$; m $$ parentPopulation $/2$; m$++)\{$

QueenBoard parent$1=$ parents.poll$()$;

QueenBoard parent$2=$ parents.poll$()$;

$//$ two offspring from each pair of parents

QueenBoard child$1=$ mate$($parent$1,$ parent$2,$ mutationRate$)$;

QueenBoard child$2=$ mate$($parent$2,$ parent$1,$ mutationRate$)$;

children.offer$($child$1)$;

children.offer$($child$2)$;

$\}$

$//$ mating is done so set the queue to the new children population

parents.clear$()$;

queue $=$ children;

$\}$

System.out.println$("$Wasn$\text{'}$t able to find a solution."$)$;

$\}$

public static QueenBoard mate$($QueenBoard p$1,$ QueenBoard p$2,$ double mutationRate$)\{$

$//$ generate random crossover point

Random random $=$ new Random$()$;

int crossoverPoint $=$ random.nextInt$(7)+1$;

int$[]$ childGenes $=$ new int$[8]$;

int$[]$ p$1$Genes $=$ p$1.$getQueens$()$;

int$[]$ p$2$Genes $=$ p$2.$getQueens$()$;

$//$ generate child genes

for $($int i $=0$; i $$ crossoverPoint; i$++)\{$

childGenes$[$i$]=$ p$1$Genes$[$i$]$;

$\}$

for $($int j $=$ crossoverPoint; j $<mtext\; id="EditorElement\_1418921"></mtext><mn\; id="EditorElement\_1418922">8</mn>$; j$++)\{$

childGenes$[$j$]=$ p$2$Genes$[$j$]$;

$\}$

$//$ generate possible mutation

if $($random$.$nextDouble$()$ mutationRate$)\{$

int mutationIndex $=$ random.nextInt$(8)$;

int newValue $=$ random.nextInt$(8)$;

childGenes$[$mutationIndex$]=$ newValue;

$\}$

return new QueenBoard$($childGenes$)$;

$\}$

$\}$