idaholab · JunyungKim · Feb 19, 2023 · Feb 19, 2023 · Feb 19, 2023 · Feb 22, 2023
diff --git a/dependencies.xml b/dependencies.xml
@@ -43,7 +43,7 @@ Note all install methods after "main" take
     <scikit-learn>1.0</scikit-learn>
     <pandas/>
     <!-- Note most versions of xarray work, but some (such as 0.20) don't -->
-    <xarray>2023</xarray>
+    <xarray>2023.12</xarray>
     <netcdf4 source="pip">1.6</netcdf4>
     <matplotlib>3.5</matplotlib>
     <statsmodels>0.13</statsmodels>
@@ -106,4 +106,4 @@ Note all install methods after "main" take
     <python>remove</python>
     <nomkl>remove</nomkl>
   </alternate>
-</dependencies>
+</dependencies>
diff --git a/developer_tools/XSDSchemas/Optimizers.xsd b/developer_tools/XSDSchemas/Optimizers.xsd
@@ -251,6 +251,8 @@
       <xsd:all>
         <xsd:element name="a"     type="xsd:float" minOccurs="0" maxOccurs='1'/>
         <xsd:element name="b"     type="xsd:float" minOccurs="0" maxOccurs='1'/>
+        <xsd:element name="scale"     type="xsd:float" minOccurs="0" maxOccurs='1'/>
+        <xsd:element name="shift"     type="xsd:float" minOccurs="0" maxOccurs='1'/>
       </xsd:all>
       <xsd:attribute name="type" type="xsd:string" />
     </xsd:complexType>

diff --git a/doc/user_manual/generated/generateOptimizerDoc.py b/doc/user_manual/generated/generateOptimizerDoc.py
@@ -152,7 +152,7 @@ def insertSolnExport(tex, obj):
       </samplerInit>
 
       <GAparams>
-        <populationSize>20</populationSize>
+        <populationSize>10</populationSize>
         <parentSelection>rouletteWheel</parentSelection>
         <reproduction>
           <crossover type="onePointCrossover">
@@ -177,32 +177,32 @@ def insertSolnExport(tex, obj):
 
       <variable name="x1">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20</initial>
+        <initial>1,2,3,4,5,6,7,8,9,10</initial>
       </variable>
 
       <variable name="x2">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,1</initial>
+        <initial>2,3,4,5,6,7,8,9,10,1</initial>
       </variable>
 
       <variable name="x3">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,1,2</initial>
+        <initial>3,4,5,6,7,8,9,10,1,2</initial>
       </variable>
 
       <variable name="x4">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,1,2,3</initial>
+        <initial>4,5,6,7,8,9,10,1,2,3</initial>
       </variable>
 
       <variable name="x5">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,1,2,3,4</initial>
+        <initial>5,6,7,8,9,10,1,2,3,4</initial>
       </variable>
 
       <variable name="x6">
         <distribution>uniform_dist_woRepl_1</distribution>
-        <initial>6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,1,2,3,4,5</initial>
+        <initial>6,7,8,9,10,1,2,3,4,5</initial>
       </variable>
 
       <objective>ans</objective>
@@ -212,6 +212,104 @@ def insertSolnExport(tex, obj):
   </Optimizers>
 \end{lstlisting}
 
+\hspace{24pt}
+Multiobjective optimization: Non Dominating Sorting GA (NSGA-II) Example:
+
+\begin{lstlisting}[style=XML]
+  <Optimizers>
+    <GeneticAlgorithm name="GAopt">
+      <samplerInit>
+        <limit>15</limit>
+        <initialSeed>42</initialSeed>
+        <writeSteps>every</writeSteps>
+        <type>min,min</type>
+      </samplerInit>
+
+      <GAparams>
+        <populationSize>10</populationSize>
+        <parentSelection>tournamentSelection</parentSelection>
+        <reproduction>
+          <crossover type="twoPointsCrossover">
+            <crossoverProb>1.0</crossoverProb>
+          </crossover>
+          <mutation type="randomMutator">
+            <mutationProb>1.0</mutationProb>
+          </mutation>
+        </reproduction>
+        <fitness type="feasibleFirst">
+        </fitness>
+        <survivorSelection>rankNcrowdingBased</survivorSelection>
+      </GAparams>
+
+      <convergence>
+        <AHDp>0.0</AHDp>
+      </convergence>
+
+      <variable name="x1">
+        <distribution>unifDist</distribution>
+      </variable>
+      <variable name="x2">
+        <distribution>unifDist</distribution>
+      </variable>
+      <variable name="x3">
+        <distribution>unifDist</distribution>
+      </variable>
+      <objective>obj1, obj2 </objective>
+      <TargetEvaluation class="DataObjects" type="PointSet">optOut</TargetEvaluation>
+      <Sampler class="Samplers" type="MonteCarlo">MC_samp</Sampler>
+    </GeneticAlgorithm>
+  </Optimizers>
+\end{lstlisting}
+"""
+
+minimalGeneticAlgorithmMultiObjective = r"""
+\hspace{24pt}
+Genetic Algorithm Example:
+\begin{lstlisting}[style=XML]
+  <Optimizers>
+    <GeneticAlgorithm name="GAopt">
+      <samplerInit>
+        <limit>15</limit>
+        <initialSeed>42</initialSeed>
+        <writeSteps>every</writeSteps>
+        <type>min,min</type>
+      </samplerInit>
+
+      <GAparams>
+        <populationSize>10</populationSize>
+        <parentSelection>tournamentSelection</parentSelection>
+        <reproduction>
+          <crossover type="twoPointsCrossover">
+            <crossoverProb>1.0</crossoverProb>
+          </crossover>
+          <mutation type="randomMutator">
+            <mutationProb>1.0</mutationProb>
+          </mutation>
+        </reproduction>
+        <fitness type="feasibleFirst">
+        </fitness>
+        <survivorSelection>rankNcrowdingBased</survivorSelection>
+      </GAparams>
+
+      <convergence>
+        <AHDp>0.0</AHDp>
+      </convergence>
+
+      <variable name="x1">
+        <distribution>unifDist</distribution>
+      </variable>
+      <variable name="x2">
+        <distribution>unifDist</distribution>
+      </variable>
+      <variable name="x3">
+        <distribution>unifDist</distribution>
+      </variable>
+      <objective>obj1, obj2 </objective>
+      <TargetEvaluation class="DataObjects" type="PointSet">optOut</TargetEvaluation>
+      <Sampler class="Samplers" type="MonteCarlo">MC_samp</Sampler>
+    </GeneticAlgorithm>
+  </Optimizers>
+\end{lstlisting}
 """
 
 minimalBayesianOptimizer = r"""