minor update of setups used in jssp experiments

thomasWeise · Jul 6, 2020 · ed6564a · ed6564a
1 parent ed86fa9
commit ed6564a
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Showing 3 changed files with 12 additions and 75 deletions.
diff --git a/README.md b/README.md
@@ -45,15 +45,15 @@ First, you need to add the following repository, which is a repository that can
 ```
 
 Than you can add the dependency on our `aitoa-code` repository into your `dependencies` section.
-Here, `0.8.58` is the current version of  `aitoa-code`.
+Here, `0.8.59` is the current version of  `aitoa-code`.
 Notice that you may have more dependencies in your `dependencies` section, say on `junit`, but here I just put the one for `aitoa-code` as example.
 
 ```xml
 <dependencies>
   <dependency>
     <groupId>com.github.thomasWeise</groupId>
     <artifactId>aitoa-code</artifactId>
-    <version>0.8.58</version>
+    <version>0.8.59</version>
   </dependency>
 </dependencies>
 ```

diff --git a/pom.xml b/pom.xml
@@ -5,7 +5,7 @@
 
 	<groupId>aitoa</groupId>
 	<artifactId>aitoa-code</artifactId>
-	<version>0.8.58</version>
+	<version>0.8.59</version>
 	<packaging>jar</packaging>
 	<name>aitoa-code</name>
 	<description>Example Source Codes from the Book "Introduction to Optimization Algorithms"</description>

diff --git a/src/main/java/aitoa/examples/jssp/EJSSPExperimentStage.java b/src/main/java/aitoa/examples/jssp/EJSSPExperimentStage.java
@@ -544,7 +544,8 @@ public void configureBuilderForProblem(
   },
 
   /**
-   * the twelfth stage: estimation of distribution algorithm
+   * the twelfth stage: estimation of distribution algorithm with
+   * local search
    */
   STAGE_12 {
 
@@ -566,83 +567,19 @@ public void configureBuilderForProblem(
           IMetaheuristic<int[], JSSPCandidateSolution>>> list =
               new ArrayList<>();
 
-      for (final int muShift : new int[] { 4, 6, 7, 8, 9, 10,
-          12 }) {
-        final int mu = 1 << muShift;
-        for (int lambdaShift = 5; lambdaShift <= 18;
-            lambdaShift++) {
-          final int lambda = 1 << lambdaShift;
+      for (int lambdaShift = 2; lambdaShift <= 6;
+          lambdaShift++) {
+        final int lambda = 1 << lambdaShift;
+        for (final int mu : new int[] { 2, 4, 8, 16 }) {
           if (mu < lambda) {
-            list.add(() -> new EDA<>(mu, lambda, //
-                new JSSPUMDAModelP(problem.instance)));
-          }
-        }
-      }
-
-      for (final int mu : new int[] { 2, 3, 4, 7, 10 }) {
-        for (int lambdaShift = 4; lambdaShift <= 8;
-            lambdaShift++) {
-          final int lambda = 1 << lambdaShift;
-          if (mu < lambda) {
-            list.add(() -> new EDAWithClearing<>(mu, lambda, //
-                new JSSPUMDAModelP(problem.instance)));
+            list.add(() -> new HybridEDAWithClearing<>(mu,
+                lambda, Integer.MAX_VALUE, //
+                new JSSPUMDAModel(problem.instance)));
           }
         }
       }
-
       return list.stream();
     }
-  },
-
-  /**
-   * the thirteenth stage: estimation of distribution algorithm
-   * with local search
-   */
-  STAGE_13 {
-
-    /**
-     * Get a stream of algorithm suppliers for a given problem
-     *
-     * @param problem
-     *          the problem
-     * @return the stream of suppliers
-     */
-    @Override
-    public
-        Stream<Supplier<
-            IMetaheuristic<int[], JSSPCandidateSolution>>>
-        getAlgorithms(//
-            final JSSPMakespanObjectiveFunction problem) {
-
-      return Stream.of(//
-          () -> new HybridEDAWithClearing<>(2, 16,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(4, 16,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(8, 16,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(2, 32,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(4, 32,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(8, 32,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(16, 32,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(4, 8,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)), //
-          () -> new HybridEDAWithClearing<>(2, 4,
-              Integer.MAX_VALUE, //
-              new JSSPUMDAModel(problem.instance)));
-    }
 
     /**
      * Configure the black box process builder for the given