[DEFECT] Setting the seed for RNG in Genetic Algorithm does not produce repeatable results

Thank you for the defect report

[X] I am using the latest version of RAVEN.
[X] I have read the Wiki.
[X] I have created a minimum, reproducible example that demonstrates the defect.

Defect Description

Setting the sampler seed within Optimizers/samplerInit/initialSeed and Samplers/MonteCarlo/samplerInit/initialSeed do not produce repeatable results.

Steps to Reproduce

Below is the template for repeating the problem. The solution changes every time it is run, despite setting the seed for the RNG in both the model and the sampler.

<?xml version="1.0" ?>
<Simulation verbosity="debug">
  <TestInfo>
    <author>user</author>
    <created>2023-12-18</created>
    <description>
       A template for running the genetic algorithm.
    </description>
  </TestInfo>
  <RunInfo>
    <JobName>analytic-optimization-coefficients</JobName>
    <Sequence>analytic-optimization-coefficients,print</Sequence>
    <WorkingDir>.</WorkingDir>
    <batchSize>10</batchSize>
  </RunInfo>

  <Steps>
    <MultiRun name="analytic-optimization-coefficients" clearRunDir="False">
      <Model class="Models" type="Code">my_raptor</Model>
      <Optimizer class="Optimizers" type="GeneticAlgorithm">genAlgo</Optimizer>
      <SolutionExport class="DataObjects" type="PointSet">opt_export</SolutionExport>
      <Output class="DataObjects" type="PointSet">optResults</Output>
      <Output class="DataObjects" type="PointSet">results</Output>
      <Output class="OutStreams" type="Print">opt_export</Output>
    </MultiRun>
    <IOStep name="print">
      <Input class="DataObjects" type="PointSet">opt_export</Input>
      <Input class="DataObjects" type="PointSet">results</Input>
      <Output class="OutStreams" type="Print">opt_export</Output>
      <Output class="OutStreams" type="Print">results</Output>
    </IOStep>
  </Steps>
  <Models>

  </Models>
  <Optimizers>
    <GeneticAlgorithm name="genAlgo">
      <samplerInit>
        <limit>10</limit>
        <initialSeed>123456</initialSeed>
        <type>min</type>
        <writeSteps>every</writeSteps>
      </samplerInit>
      <GAparams>
        <populationSize>20</populationSize>
        <parentSelection>rouletteWheel</parentSelection>
        <reproduction>
          <crossover type="onePointCrossover">
            <crossoverProb>0.8</crossoverProb>
          </crossover>
          <mutation type="swapMutator">
            <mutationProb>0.8</mutationProb>
          </mutation>
        </reproduction>
        <fitness type="invLinear">
          <a>1.0</a>
          <b>0.0</b>
        </fitness>
        <survivorSelection>fitnessBased</survivorSelection>
      </GAparams>
      <objective>obj</objective>
      <TargetEvaluation class="DataObjects" type="PointSet">optResults</TargetEvaluation>
      <Sampler class="Samplers" type="MonteCarlo">MC_samp</Sampler>
      <variable name="Xwidth">
        <distribution>XwidthDist</distribution>
      </variable>
      <variable name="Ywidth">
        <distribution>YwidthDist</distribution>
      </variable>
    </GeneticAlgorithm>
  </Optimizers>
  <Samplers>
    <MonteCarlo name="MC_samp">
      <samplerInit>
        <limit>20</limit>
        <initialSeed>123456</initialSeed>
      </samplerInit>
      <variable name="Xwidth">
        <distribution>XwidthDist</distribution>
      </variable>
      <variable name="Ywidth">
        <distribution>YwidthDist</distribution>
      </variable>
    </MonteCarlo>
  </Samplers>
  <Functions>
  </Functions>
  <Distributions>
    <Uniform name="XwidthDist">
      <lowerBound>0.0</lowerBound>
      <upperBound>1.0</upperBound>
    </Uniform>
    <Uniform name="YwidthDist">
      <lowerBound>1.0</lowerBound>
      <upperBound>4.5</upperBound>
    </Uniform>
  </Distributions>
  <VariableGroups>
    <Group name="invars">Xwidth,Ywidth</Group>
    <Group name="outvars">targetVal,time,hdfFile,obj</Group>
    <Group name="all">Xwidth,Ywidth,obj,targetVal,time</Group>
  </VariableGroups>
  <DataObjects>
    <PointSet name="results">
      <Input>Xwidth,Ywidth</Input>
      <Output>hdfFile,obj,targetVal,time</Output>
    </PointSet>
    <PointSet name="optResults">
      <Input>Xwidth,Ywidth</Input>
      <Output>obj,targetVal,time</Output>
    </PointSet>
    <PointSet name="opt_export">
      <Input>trajID</Input>
      <Output>all,age,batchId,fitness,iteration,accepted,conv_objective</Output>
    </PointSet>
  </DataObjects>
  <OutStreams>
    <Print name="results" dir="analytic-optimization-coefficients">
      <type>csv</type>
      <source>results</source>
      <what>input,output</what>
    </Print>
    <Print name="opt_export" dir="analytic-optimization-coefficients">
      <type>csv</type>
      <source>opt_export</source>
      <clusterLabel>trajID</clusterLabel>
      <what>input,output</what>
    </Print>
  </OutStreams>
</Simulation>

Expected Behavior

That setting the seed for the RNG would produce repeatable results.

Screenshots and Input Files

No response

OS

Linux

OS Version

No response

Dependency Manager

PIP

For Change Control Board: Issue Review

[ ] Is it tagged with a type: defect or task?
[ ] Is it tagged with a priority: critical, normal or minor?
[ ] If it will impact requirements or requirements tests, is it tagged with requirements?
[ ] If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
[ ] Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure

[ ] If the issue is a defect, is the defect fixed?
[ ] If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
[ ] If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
[ ] If the issue is a defect, does it impact the latest release branch? If yes, is there any issue tagged with release (create if needed)?
[ ] If the issue is being closed without a pull request, has an explanation of why it is being closed been provided?

idaholab / raven

[DEFECT] Setting the seed for RNG in Genetic Algorithm does not produce repeatable results #2232