public code v1

plugins/afryca.consensusmodel.palomares2014cluster/.classpath

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+<?xml version="1.0" encoding="UTF-8"?>
+<classpath>
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.8"/>
+	<classpathentry kind="con" path="org.eclipse.pde.core.requiredPlugins"/>
+	<classpathentry kind="src" path="src"/>
+	<classpathentry kind="output" path="bin"/>
+</classpath>

plugins/afryca.consensusmodel.palomares2014cluster/.gitignore

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+/bin/

plugins/afryca.consensusmodel.palomares2014cluster/.project

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+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+	<name>afryca.consensusmodel.palomares2014cluster</name>
+	<comment></comment>
+	<projects>
+	</projects>
+	<buildSpec>
+		<buildCommand>
+			<name>org.eclipse.jdt.core.javabuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+		<buildCommand>
+			<name>org.eclipse.pde.ManifestBuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+		<buildCommand>
+			<name>org.eclipse.pde.SchemaBuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+		<buildCommand>
+			<name>org.eclipse.m2e.core.maven2Builder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+	</buildSpec>
+	<natures>
+		<nature>org.eclipse.m2e.core.maven2Nature</nature>
+		<nature>org.eclipse.pde.PluginNature</nature>
+		<nature>org.eclipse.jdt.core.javanature</nature>
+	</natures>
+</projectDescription>

plugins/afryca.consensusmodel.palomares2014cluster/.settings/org.eclipse.jdt.core.prefs

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+eclipse.preferences.version=1
+org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
+org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.8
+org.eclipse.jdt.core.compiler.compliance=1.8
+org.eclipse.jdt.core.compiler.problem.assertIdentifier=error
+org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
+org.eclipse.jdt.core.compiler.source=1.8

plugins/afryca.consensusmodel.palomares2014cluster/.settings/org.eclipse.m2e.core.prefs

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+activeProfiles=
+eclipse.preferences.version=1
+resolveWorkspaceProjects=true
+version=1

plugins/afryca.consensusmodel.palomares2014cluster/META-INF/MANIFEST.MF

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+Manifest-Version: 1.0
+Bundle-ManifestVersion: 2
+Bundle-Name: %Bundle-Name
+Bundle-SymbolicName: afryca.consensusmodel.palomares2014cluster;singleton:=true
+Bundle-Version: 1.0.0.qualifier
+Bundle-RequiredExecutionEnvironment: JavaSE-1.8
+Require-Bundle: afryca.consensusmodel
+Bundle-ActivationPolicy: lazy
+Automatic-Module-Name: afryca.consensusmodel.palomares2014cluster

plugins/afryca.consensusmodel.palomares2014cluster/OSGI-INF/l10n/bundle.properties

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+#Properties file for afryca.consensusmodel.palomares2014cluster
+afryca.consensusmodel.palomares2014cluster.information  = Paper:Palomares, I., Martinez, L., & Herrera, F. A consensus model to detect and manage noncooperative behaviors in large-scale group decision making. IEEE Transactions on Fuzzy Systems, 22(3), pp. 516-530, 2014\\n I. Palomares \\n Consensus model suitable to manage large scales of decision makers, which incorporates a fuzzy clustering-based scheme to detect and manage individual and subgroup noncooperative behaviors
+afryca.consensusmodel.palomares2014cluster.MainFeatures = Fuzzy preference relations \\n Clustering  \\n Detect non cooperative behaviours \\ Full weigth penalizing \\n Feedback
+afryca.consensusmodel.palomares2014cluster.Name = I. Palomares et al. (TFS-2014)
+afryca.consensusmodel.palomares2014cluster.Observations = No observations
+afryca.consensusmodel.palomares2014cluster.variable.max_rounds.description = Maximum Number of rounds
+afryca.consensusmodel.palomares2014cluster.variable.epsilon.description = Aceptability threshold
+afryca.consensusmodel.palomares2014cluster.variable.distance_measure_minkowski.description = Minkowski distance measure
+afryca.consensusmodel.palomares2014cluster.variable.cluster_similiraty_threshold.description = Threshold similarity between clusters
+afryca.consensusmodel.palomares2014cluster.variable.min_distance_cluster.description = Minimun distance between similar clusters
+afryca.consensusmodel.palomares2014cluster.variable.outlier_threshold.description = Outlier detection mechanism
+afryca.consensusmodel.palomares2014cluster.variable.outlier_membership.description = Cluster membership threshold for outliers
+afryca.consensusmodel.palomares2014cluster.variable.consensus_threshold.description = Consensus threshold
+Bundle-Name = Palomares2014cluster

plugins/afryca.consensusmodel.palomares2014cluster/OSGI-INF/l10n/bundle_es.properties

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+#Properties file for afryca.consensusmodel.palomares2014cluster
+afryca.consensusmodel.palomares2014cluster.information  = Paper:Palomares, I., Martinez, L., & Herrera, F. A consensus model to detect and manage noncooperative behaviors in large-scale group decision making. IEEE Transactions on Fuzzy Systems, 22(3), pp. 516-530, 2014\\n I. Palomares \\n Consensus model suitable to manage large scales of decision makers, which incorporates a fuzzy clustering-based scheme to detect and manage individual and subgroup noncooperative behaviors
+afryca.consensusmodel.palomares2014cluster.MainFeatures = Clustering  \\n Detección de comportamientos no cooperativos \\ Penalizacion de pesos completa \\n Retroalimentacion
+afryca.consensusmodel.palomares2014cluster.Name = I. Palomares et al. (TFS-2014)
+afryca.consensusmodel.palomares2014cluster.Observations = No observations
+afryca.consensusmodel.palomares2014cluster.variable.max_rounds.description = Número mmáximo de rondas
+afryca.consensusmodel.palomares2014cluster.variable.epsilon.description = Umbral de aceptabilidad
+afryca.consensusmodel.palomares2014cluster.variable.distance_measure_minkowski.description = Medida de distancia Minkowski
+afryca.consensusmodel.palomares2014cluster.variable.cluster_similiraty_threshold.description = Umbral de similitud entre clasters
+afryca.consensusmodel.palomares2014cluster.variable.min_distance_cluster.description = Distancia minima entre clusters parecidos
+afryca.consensusmodel.palomares2014cluster.variable.outlier_threshold.description = Umbral del mecanismo de expertos solitarios(outliers)
+afryca.consensusmodel.palomares2014cluster.variable.outlier_membership.description = Umbral de pertenecia a un claster para expertos solitarios(outliers)
+afryca.consensusmodel.palomares2014cluster.variable.consensus_threshold.description = Umbral de consenso
+Bundle-Name = Palomares2014cluster

plugins/afryca.consensusmodel.palomares2014cluster/build.properties

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+source.. = src/
+output.. = bin/
+bin.includes = META-INF/,\
+               .,\
+               plugin.xml,\
+               OSGI-INF/l10n/bundle.properties,\
+               OSGI-INF/

plugins/afryca.consensusmodel.palomares2014cluster/plugin.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<?eclipse version="3.4"?>
+<plugin>
+   <extension
+         point="afryca.consensusmodel">
+       <ConsensusModel
+             ConsensusModel="afryca.consensusmodel.Palomares2014Cluster"
+             Information="%afryca.consensusmodel.palomares2014cluster.information"
+             MainFeatures="%afryca.consensusmodel.palomares2014cluster.MainFeatures"
+             Multicriteria="false"
+             Name="%afryca.consensusmodel.palomares2014cluster.Name"
+             Observations="%afryca.consensusmodel.palomares2014cluster.Observations"
+             Structure="afryca.fpr"
+             WithFeedback="true"
+             id="Palomares2014Cluster">
+         <Variable
+               default_value="15"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.max_rounds.description"
+               id="max_rounds"
+               is_array="false"
+               is_internal="false"
+               type="Integer">
+            <Restriction
+                  type="lower_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.05"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.epsilon.description"
+               id="epsilon"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="1"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.distance_measure_minkowski.description"
+               id="distance_measure_minkowski"
+               is_array="false"
+               is_internal="false"
+               type="Integer">
+            <Restriction
+                  type="lower_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.9"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.cluster_similiraty_threshold.description "
+               id="cluster_similiraty_threshold"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+            <Restriction
+                  type="upper_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.01"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.min_distance_cluster.description"
+               id="min_distance_cluster"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+            <Restriction
+                  type="upper_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.75"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.outlier_threshold.description"
+               id="outlier_threshold"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+            <Restriction
+                  type="upper_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.4"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.outlier_membership.description"
+               id="outlier_membership"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+            <Restriction
+                  type="upper_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+         <Variable
+               default_value="0.85"
+               description="%afryca.consensusmodel.palomares2014cluster.variable.consensus_threshold.description"
+               id="consensus_threshold"
+               is_array="false"
+               is_internal="false"
+               type="Float">
+            <Restriction
+                  type="lower_limit"
+                  value="0">
+            </Restriction>
+            <Restriction
+                  type="upper_limit"
+                  value="1">
+            </Restriction>
+         </Variable>
+      </ConsensusModel>
+   </extension>   
+
+</plugin>

plugins/afryca.consensusmodel.palomares2014cluster/src/afryca/consensusmodel/Palomares2014Cluster.java

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+package afryca.consensusmodel;
+
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.Iterator;
+import java.util.LinkedList;
+import java.util.List;
+
+import afryca.cm.CM;
+import afryca.consensusmodel.cluster.ClusterFPR;
+import afryca.consensusmodel.clustering.FuzzyCMeansFPR;
+import afryca.consensusmodel.clustering.FuzzyCMeansFPRKatsavounidis;
+import afryca.consensusmodel.definition.EResultElements;
+import afryca.consensusmodel.definition.ERoundResult;
+import afryca.fpr.FPR;
+import afryca.structure.Structure;
+import afryca.structure.pair.Pair;
+
+public class Palomares2014Cluster extends ConsensusModel {
+
+	private static final String CONSENSUS_MODEL_NAME = "I. Palomares IEEE. (2014) Clustering"; //$NON-NLS-1$
+
+	private static final String DISTANCE_MEASURE_MINKOWSKI = "distance_measure_minkowski"; //$NON-NLS-1$ //1
+	private static final String CLUSTER_SIMILARITY_THRESHOLD = "cluster_similiraty_threshold"; //$NON-NLS-1$ //0.9
+	private static final String MIN_DISTANCE_CLUSTER = "min_distance_cluster"; //$NON-NLS-1$ //0.01
+	private static final String OUTLIER_THRESHOLD = "outlier_threshold"; //$NON-NLS-1$ //0.75
+	private static final String OULIER_MEMBERSHIP = "outlier_membership"; //$NON-NLS-1$ //0.4
+	private static final String MAX_ROUNDS = "max_rounds"; //$NON-NLS-1$ //15
+	private static final String CONSENSUS_THRESHOLD = "consensus_threshold";//$NON-NLS-1$ //0.85
+	private static final String EPSILON = "epsilon"; //$NON-NLS-1$ //
+
+	private int p;
+	private float cSimThreshold;
+	private float minDisCluster;
+	private float outThreshold;
+	private float outMembership;
+	private float epsilon;
+	private int maxRounds;
+	private float consensusThreshold;
+
+	private float consensusDegree;
+
+	private int currentRound;
+
+	private int[] advises;
+	private Float[] weights;
+
+	private CM consensusMatrix;
+	private Float[] ca;
+
+	private List<ClusterFPR> postClusters;
+
+	@Override
+	protected void setModelConfiguration() {
+
+	}
+
+	@Override
+	protected void obtainConfigurationValues() {
+		p = (Integer) configuration.getValue(DISTANCE_MEASURE_MINKOWSKI);
+		cSimThreshold = (Float) configuration.getValue(CLUSTER_SIMILARITY_THRESHOLD);
+		minDisCluster = (Float) configuration.getValue(MIN_DISTANCE_CLUSTER);
+		outThreshold = (Float) configuration.getValue(OUTLIER_THRESHOLD);
+		outMembership = (Float) configuration.getValue(OULIER_MEMBERSHIP);
+		epsilon = (Float) configuration.getValue(EPSILON);
+		maxRounds = (Integer) configuration.getValue(MAX_ROUNDS);
+		consensusThreshold = (Float) configuration.getValue(CONSENSUS_THRESHOLD);
+		postClusters = new LinkedList<ClusterFPR>();
+
+		initializeAdvises();
+		initializeWeights();
+	}
+
+	private void initializeAdvises() {
+		advises = new int[experts.length];
+		for (int i = 0; i < advises.length; i++) {
+			advises[i] = 0;
+		}
+	}
+
+	private void initializeWeights() {
+		weights = new Float[experts.length];
+		for (int i = 0; i < weights.length; i++) {
+			weights[i] = 1f;
+		}
+	}
+	
+	@Override
+	protected Float[][][] obtainVisualizeValues() {
+		computeCollective();
+		computeConsensusDegree();
+
+		Float[][][] preferencesGroupVisualization = new Float[numberOfExperts + 1][numberOfAlternatives][numberOfAlternatives];
+		for (int k = 0; k < numberOfExperts+1; k++) {
+			preferencesGroupVisualization[k] = preferences[k].obtainVisualizeValues();
+		}
+		
+		return preferencesGroupVisualization;
+	}
+	
+	@Override
+	protected void preFirstSaveRoundResults() {
+		preSaveRoundResult(0, preferences,obtainVisualizeValues(), consensusDegree);
+
+		result.put(EResultElements.initial_consensus_degree, consensusDegree);
+		result.put(EResultElements.maxround, maxRounds);
+		result.put(EResultElements.consensus_threshold, consensusThreshold);
+		result.put(EResultElements.consensus_model, CONSENSUS_MODEL_NAME);
+	}
+
+	@Override
+	protected void preSaveRoundResults() {
+		preSaveRoundResult(currentRound + 1, preferences,obtainVisualizeValues(), consensusDegree);
+		roundsResults.get(roundsResults.size() - 1).put(ERoundResult.clusters, postClusters);
+	}
+
+	@Override
+	protected void consensusRound() {
+		int nChanges = 0;
+
+		computeCollective();
+		computeConsensusDegree();
+
+		if (consensusDegree < consensusThreshold) {
+
+			CM[] proximityMatrices = ConsensusEngine.similarityMatricesRespectCollective(numberOfExperts,numberOfAlternatives, preferences, preferences[numberOfExperts]);
+			Boolean[][] pairsOfAlternativesToChange = identifyPairsOfAlternativesToChange(numberOfAlternatives, ca,	consensusDegree, consensusMatrix);
+			CM proximityAverageMatrix = ConsensusEngine.similarityAverageMatrix(numberOfExperts, numberOfAlternatives,proximityMatrices);
+			Boolean[][][] changePairsOfAlternativesByExperts = identifyChangePairsOfAlternativesByExperts(pairsOfAlternativesToChange, proximityMatrices,proximityAverageMatrix);
+			EChangeType[][][] changes = calculeChanges(changePairsOfAlternativesByExperts);
+			nChanges = countChanges(changes);
+			double[] changesIndividual = getNChanges(nChanges);
+			advises = new int[numberOfExperts];
+			makeChanges(changes, changesIndividual);
+
+			postClusters = FuzzyCMeansFPRKatsavounidis.doClusteringFuzzyCMeansKatsavounidis(alternatives, experts, (Structure[]) preferences, p);
+			
+			List<Integer> nonCooperativeClusters=detectGroupNonCooperativeBehavior();
+
+			if(!nonCooperativeClusters.isEmpty()){
+				updateSubGroupWeights(nonCooperativeClusters);
+			}
+
+			if (consensusDegree > outThreshold) {
+				List<Integer> expertsNonCooperative=detectIndividualNonCooperativeBehavior();
+				if(!expertsNonCooperative.isEmpty()){
+					updateIndividualWeights(expertsNonCooperative);
+				}
+			}
+
+			currentRound++;
+		}
+
+
+	}
+
+	private void computeCollective() {
+		if (equalWeigths(weights)) {
+			preferences[numberOfExperts] = ConsensusEngine.groupPreferences(numberOfExperts, numberOfAlternatives,preferences);
+		} else {
+			preferences[numberOfExperts] = ConsensusEngine.groupPreferencesWeights(numberOfExperts,	numberOfAlternatives, preferences, weights);
+		}
+	}
+
+	private void computeConsensusDegree() {
+
+		CM[][] sm_matrices = ConsensusEngine.similarityMatrices(numberOfExperts, numberOfAlternatives, preferences);
+
+		if (equalWeigths(weights)) {
+			consensusMatrix = ConsensusEngine.consensusMatrixBasedOnSimilarityBetweenFPRs(numberOfExperts, numberOfAlternatives, sm_matrices);
+		} else {
+			consensusMatrix = ConsensusEngine.consensusMatrixBasedOnSimilarityBetweenFPRsMinWeights(numberOfExperts, numberOfAlternatives, sm_matrices, weights);
+		}
+		ca = ConsensusEngine.computeAlternativesConsensus(numberOfAlternatives, consensusMatrix);
+		consensusDegree = ConsensusEngine.consensusBasedOnAlternativesConsensus(numberOfAlternatives, ca);
+
+	}
+
+	private boolean equalWeigths(Float[] weights) {
+
+		for (int i = 0; i < weights.length - 1; i++) {
+			if (Float.compare(weights[i], weights[i + 1]) !=0 ) {
+				return false;
+			}
+
+		}
+		return true;
+	}
+
+	@Override
+	protected void posSaveRoundResults() {
+		posSaveRoundResult(preferences,obtainVisualizeValues(), consensusDegree, advises, preferences[numberOfExperts]);
+
+	}
+
+	@Override
+	protected boolean mustBeCarriedOutAnotherRound() {
+		return (((float) consensusDegree < consensusThreshold) && (currentRound < maxRounds));
+	}
+
+	@Override
+	protected void saveExecutionResults() {
+		this.configuration.setValue(PREFERENCES, preferences);
+		result.put(EResultElements.number_of_rounds_required, currentRound);
+		result.put(EResultElements.consensus_degree_achieved, consensusDegree);
+	}
+
+	/**
+	 * Identify pairs of alternatives to change
+	 * 
+	 * @param alternatives
+	 *            Number of alternatives
+	 * @param ac
+	 *            Alternatives consensus
+	 * @param cr
+	 *            Overall consensus degree
+	 * @param cm
+	 *            Consensus matrix
+	 * @return Pairs of alternatives to change
+	 */
+	private static Boolean[][] identifyPairsOfAlternativesToChange(Integer alternatives, Float[] ac, Float cr, CM cm) {
+
+		Boolean[][] result = new Boolean[alternatives][alternatives];
+
+		Boolean change;
+		for (int i = 0; i < alternatives; i++) {
+			for (int j = 0; j < alternatives; j++) {
+				change = false;
+				if (i != j) {
+					if (ac[i] < cr) {
+						if ((float) cm.getValue(i, j) < cr) {
+							change = true;
+						}
+					}
+				}
+				result[i][j] = change;
+			}
+		}
+
+		return result;
+	}
+
+	/**
+	 * Identify change in pairs of alternatives by experts
+	 * 
+	 * @param experts
+	 *            Number of experts
+	 * @param alternatives
+	 *            Number of alternatives
+	 * @param pairsOfAlternativesToChange
+	 *            Pairs of alternatives to change
+	 * @param proximityMatrices
+	 *            Proximity matrices
+	 * @param proximityAverageMatrix
+	 *            Proximity average matrix
+	 * @return Change in pairs of alternatives by experts
+	 */
+	private Boolean[][][] identifyChangePairsOfAlternativesByExperts(Boolean[][] pairsOfAlternativesToChange, CM[] proximityMatrices, CM proximityAverageMatrix) {
+
+		Boolean[][][] result = new Boolean[experts.length][alternatives.length][alternatives.length];
+
+		Boolean change;
+		for (int expert = 0; expert < experts.length; expert++) {
+			for (int i = 0; i < alternatives.length; i++) {
+				for (int j = 0; j < alternatives.length; j++) {
+					change = false;
+					if (pairsOfAlternativesToChange[i][j]) {
+						if ((float) proximityMatrices[expert].getValue(i, j) < (float) proximityAverageMatrix.getValue(i, j)) {
+							change = true;
+						}
+					}
+					result[expert][i][j] = change;
+				}
+			}
+		}
+		return result;
+	}
+
+	/**
+	 * Calcule changes to make
+	 * 
+	 * @param experts
+	 *            Number of experts
+	 * @param alternatives
+	 *            Number of alternatives
+	 * @param changePairsOfAlternativesByExperts
+	 *            Change in pairs of alternatives by experts
+	 * @param preferences
+	 *            All FPR.
+	 * @param epsilon
+	 *            Acceptability threshold
+	 * @return Changes to make
+	 */
+	private EChangeType[][][] calculeChanges(Boolean[][][] changePairsOfAlternativesByExperts) {
+		EChangeType[][][] result = new EChangeType[experts.length][alternatives.length][alternatives.length];
+
+		Float difference;
+		for (int expert = 0; expert < experts.length; expert++) {
+			for (int i = 0; i < alternatives.length; i++) {
+				for (int j = 0; j < alternatives.length; j++) {
+					if (changePairsOfAlternativesByExperts[expert][i][j]) {
+						difference = (float) preferences[expert].getValue(i, j)
+								- (Float) preferences[experts.length].getValue(i, j);
+						if (difference < (-epsilon)) {
+							result[expert][i][j] = EChangeType.Increase;
+						} else if (difference > epsilon) {
+							result[expert][i][j] = EChangeType.Decrease;
+						} else {
+							result[expert][i][j] = EChangeType.NotChange;
+						}
+					} else {
+						result[expert][i][j] = EChangeType.NotChange;
+					}
+				}
+			}
+		}
+
+		return result;
+	}
+
+	/**
+	 * Make preferences changes
+	 * 
+	 * @param experts
+	 *            Number of experts
+	 * @param alternatives
+	 *            Number of alternatives
+	 * @param preferences
+	 *            All FPR
+	 * @param changes
+	 *            Changes to make
+	 * @param changesIndividual
+	 *            Update coefficient
+	 * @param advises
+	 */
+	private void makeChanges( EChangeType[][][] changes,double[] changesIndividual) {
+
+		float value;
+		EChangeType change;
+		int numChanges = 0;
+		for (int expert = 0; expert < experts.length; expert++) {
+			for (int i = 0; i < alternatives.length; i++) {
+				for (int j = 0; j < alternatives.length; j++) {
+					change = changes[expert][i][j];
+					if (change != EChangeType.NotChange) {
+						if (changesIndividual[numChanges] != 0) {
+							value = (Float) preferences[expert].getValue(i, j);
+							if (change == EChangeType.Increase) {
+								value+=changesIndividual[numChanges];
+								if (value > 1f) {
+									value = 1f;
+								} else if(value < 0f) {
+									value = 0f;
+								}
+							} else if (change == EChangeType.Decrease) {
+								value-=changesIndividual[numChanges];
+								if (value > 1f) {
+									value = 1f;
+								} else if(value < 0f) {
+									value = 0f;
+								}
+							}
+							((FPR) preferences[expert]).setValueSymmetrically(i, j, value);
+							advises[expert] = 1;
+						}
+						numChanges++;
+					}
+				}
+			}
+		}
+	}
+
+	private int countChanges(EChangeType[][][] result) {
+		int n = 0;
+		for (int expert = 0; expert < result.length; expert++) {
+			for (int i = 0; i < result[expert].length; i++) {
+				for (int j = 0; j < result[expert][i].length; j++) {
+					if (result[expert][i][j] != EChangeType.NotChange) {
+						n++;
+					}
+				}
+			}
+		}
+		return n;
+	}
+
+	@SuppressWarnings("unchecked")
+	private List<Integer> detectGroupNonCooperativeBehavior() {
+		List<ClusterFPR> lastClusters=(List<ClusterFPR>) roundsResults.get(roundsResults.size() - 1).get(ERoundResult.clusters);
+		
+		ArrayList<ArrayList<Double>> degreeLast = new ArrayList<ArrayList<Double>>();
+		ArrayList<ArrayList<Double>> degreePost = new ArrayList<ArrayList<Double>>();
+		
+		double increment = 0;
+		
+		List<Pair<Integer,Integer>> sameClusterList=new ArrayList<>();
+		List<Pair<Integer,Integer>> furtherDistanceClusterList=new ArrayList<>();
+		
+		HashSet<Integer> nonClustersHash=new HashSet<>();
+		List<Integer> nonCooperativeClusters=new ArrayList<>();
+
+		if (lastClusters != null) {
+
+			// Detect subgroups non coperative
+			
+			//SIMILAR CLUSTER COMPOSITION
+			degreePost=computeExpertsMembershipDegrees((Structure[]) preferences, postClusters);
+			degreeLast=computeExpertsMembershipDegrees(((Structure[]) roundsResults.get(roundsResults.size() - 1).get(ERoundResult.pre_preferences)),lastClusters);
+			
+			for (int i = 1; i < postClusters.size(); i++) {//INIT i=1, not compare the first cluster(centroid=collective)
+				for (int j = i; j < lastClusters.size(); j++) {
+					increment = 0;
+					for (int k = 0; k < experts.length; k++) {
+						increment += Math.abs(degreePost.get(k).get(i) - degreeLast.get(k).get(j));
+					}
+					if ((1 - (increment / experts.length)) >= cSimThreshold) {//IS A SIMILAR CLUSTER
+						sameClusterList.add(new Pair<Integer,Integer>(i,j));
+					}
+				}
+			}
+			
+			//FURTHER DISTANCE TO Pc
+			if (!sameClusterList.isEmpty()) {
+				for (int i=0;i<sameClusterList.size();i++) {
+					double postDistance = ConsensusEngine.distanceMinkowski((FPR) postClusters.get(0).getCentroid(), (FPR) postClusters.get(sameClusterList.get(i).getLeft()).getCentroid(), p);
+					double lastDistance = ConsensusEngine.distanceMinkowski((FPR) lastClusters.get(0).getCentroid(), (FPR) lastClusters.get(sameClusterList.get(i).getRight()).getCentroid(), p);
+
+					if (postDistance > minDisCluster && postDistance >= lastDistance) {
+						furtherDistanceClusterList.add(sameClusterList.get(i));
+					}
+				}
+			}
+			
+			//MEMBERSHIP ASSEMBLING
+			if (!furtherDistanceClusterList.isEmpty()) {
+				for (int i=0;i<furtherDistanceClusterList.size();i++) {
+					double sumDegreeLast = 0;
+					double sumDegreePost = 0;
+
+					for (int j = 0; j < experts.length; j++) {
+						sumDegreePost += degreePost.get(j).get(furtherDistanceClusterList.get(i).getLeft());
+						sumDegreeLast += degreeLast.get(j).get(furtherDistanceClusterList.get(i).getRight());
+
+					}
+
+					if (sumDegreePost > sumDegreeLast) {
+						nonClustersHash.add(furtherDistanceClusterList.get(i).getLeft());
+					}
+
+				}
+				double sumDegreeLastCollective = 0;
+				double sumDegreePostCollective = 0;
+				for (int j = 0; j < experts.length; j++) {
+					sumDegreePostCollective += degreePost.get(j).get(0);
+					sumDegreeLastCollective += degreeLast.get(j).get(0);
+
+				}
+				if (sumDegreePostCollective < sumDegreeLastCollective) {
+					nonClustersHash.add(0); 
+				}
+
+			}
+
+		}
+		
+		for( Iterator<Integer> it = nonClustersHash.iterator(); it.hasNext(); ) {
+			Object obj = it.next(); 
+			int c = (int)obj; 
+			nonCooperativeClusters.add(c);
+		} 
+		
+		
+
+		return nonCooperativeClusters;
+	}
+
+	private List<Integer> detectIndividualNonCooperativeBehavior() {
+		ArrayList<ArrayList<Double>> degreePost = new ArrayList<ArrayList<Double>>();
+		List<Integer> expertsAux = new ArrayList<>();
+		List<Integer> expertsNonCooperative = new ArrayList<>();
+		
+		degreePost=computeExpertsMembershipDegrees((Structure[]) preferences, postClusters);
+		
+		
+		for (int i = 0; i < experts.length; i++) {
+			boolean membership=true;
+			for (Double degree : degreePost.get(i)) {
+				if (degree < outMembership) {
+					membership=false;
+				}
+			}
+			if(!membership){
+				expertsAux.add(i);
+			}
+		}
+
+		if (!expertsAux.isEmpty()) {
+			double d = 0;
+			for (int i = 0; i < experts.length; i++) {
+
+				d += ConsensusEngine.distanceMinkowski((FPR) preferences[i], (FPR) preferences[experts.length],p);
+
+			}
+			d = d / experts.length;
+
+			for (int expert : expertsAux) {
+				if (ConsensusEngine.distanceMinkowski((FPR) preferences[expert], (FPR) preferences[experts.length],p) > d) {
+					expertsNonCooperative.add(expert);
+				} else {
+			
+					double distanceMinkPost = ConsensusEngine.distanceMinkowski((FPR) preferences[expert],(FPR) preferences[experts.length], p);
+					double distanceMinkLast = ConsensusEngine.distanceMinkowski((FPR) ((Structure[]) roundsResults.get(roundsResults.size() - 1).get(ERoundResult.pre_preferences))[expert],
+							(FPR) ((Structure[]) roundsResults.get(roundsResults.size() - 1).get(ERoundResult.pre_preferences))[experts.length],p);
+					if (distanceMinkPost > distanceMinkLast) {
+						expertsNonCooperative.add(expert);
+					}
+				}
+			}
+		}
+
+		return expertsNonCooperative;
+	}
+	
+	private ArrayList<ArrayList<Double>> computeExpertsMembershipDegrees(Structure[] preferences, List<ClusterFPR> cluster){
+		ArrayList<ArrayList<Double>> degree = new ArrayList<ArrayList<Double>>();
+		for (int i = 0; i < experts.length; i++) {
+			degree.add(FuzzyCMeansFPR.computeExpertMembershipDegrees(i, (FPR) preferences[i], p,cluster));
+		}
+		return degree;
+	}
+
+	private void updateSubGroupWeights(List<Integer> nonCooperativeClusters) {
+		for (Integer cluster : nonCooperativeClusters) {
+				for (Integer expert: postClusters.get(cluster).getExperts()) {
+					weights[expert]=updateWeight(expert);
+				}
+		}
+	}
+
+	private void updateIndividualWeights(List<Integer> expertsNonCooperative) {
+
+		for (Integer expert : expertsNonCooperative) {
+			weights[expert]=updateWeight(expert);
+		}
+
+	}
+
+	private float updateWeight(int expert) {
+		
+		double maxDist = Double.MIN_VALUE, dist = 0;
+		for (int i = 0; i < experts.length; i++) {
+			dist = ConsensusEngine.distanceMinkowski((FPR) preferences[i], (FPR) preferences[experts.length],p);
+			if (maxDist < dist) {
+				maxDist = dist;
+			}
+		}
+
+		dist = ConsensusEngine.distanceMinkowski((FPR) preferences[expert],	(FPR) preferences[experts.length], p);
+		return (float) (weights[expert] * (1 - (dist / maxDist)));
+
+	}
+
+	
+
+}
+

plugins/afryca.consensusmodel.palomares2014cluster/target/MANIFEST.MF

@@ -0,0 +1,11 @@
+Manifest-Version: 1.0
+Bundle-ManifestVersion: 2
+Bundle-Name: %Bundle-Name
+Bundle-SymbolicName: afryca.consensusmodel.palomares2014cluster;singleto
+ n:=true
+Bundle-Version: 1.0.0.202101221157
+Bundle-RequiredExecutionEnvironment: JavaSE-1.8
+Require-Bundle: afryca.consensusmodel
+Bundle-ActivationPolicy: lazy
+Automatic-Module-Name: afryca.consensusmodel.palomares2014cluster
+

plugins/afryca.consensusmodel.palomares2014cluster/target/local-artifacts.properties

@@ -0,0 +1,4 @@
+#Fri Jan 22 13:01:32 CET 2021
+artifact.main=C\:\\Users\\\u00C1lvaro\\Workspaces\\afryca_2020\\afryca\\plugins\\afryca.consensusmodel.palomares2014cluster\\target\\afryca.consensusmodel.palomares2014cluster-1.0.0-SNAPSHOT.jar
+artifact.attached.p2artifacts=C\:\\Users\\\u00C1lvaro\\Workspaces\\afryca_2020\\afryca\\plugins\\afryca.consensusmodel.palomares2014cluster\\target\\p2artifacts.xml
+artifact.attached.p2metadata=C\:\\Users\\\u00C1lvaro\\Workspaces\\afryca_2020\\afryca\\plugins\\afryca.consensusmodel.palomares2014cluster\\target\\p2content.xml

plugins/afryca.consensusmodel.palomares2014cluster/target/maven-archiver/pom.properties

@@ -0,0 +1,3 @@
+artifactId=afryca.consensusmodel.palomares2014cluster
+groupId=afryca.group
+version=1.0.0-SNAPSHOT

plugins/afryca.consensusmodel.palomares2014cluster/target/p2artifacts.xml

@@ -0,0 +1,13 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<?artifactRepository version='1.1.0'?>
+<artifacts size='1'>
+  <artifact classifier='osgi.bundle' id='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157'>
+    <properties size='5'>
+      <property name='artifact.size' value='12369'/>
+      <property name='download.size' value='12369'/>
+      <property name='maven-groupId' value='afryca.group'/>
+      <property name='maven-artifactId' value='afryca.consensusmodel.palomares2014cluster'/>
+      <property name='maven-version' value='1.0.0-SNAPSHOT'/>
+    </properties>
+  </artifact>
+</artifacts>

plugins/afryca.consensusmodel.palomares2014cluster/target/p2content.xml

@@ -0,0 +1,45 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<units size='1'>
+  <unit id='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157' generation='2'>
+    <update id='afryca.consensusmodel.palomares2014cluster' range='[0.0.0,1.0.0.202101221157)' severity='0'/>
+    <properties size='6'>
+      <property name='es.Bundle-Name' value='Palomares2014cluster'/>
+      <property name='df_LT.Bundle-Name' value='Palomares2014cluster'/>
+      <property name='org.eclipse.equinox.p2.name' value='%Bundle-Name'/>
+      <property name='maven-groupId' value='afryca.group'/>
+      <property name='maven-artifactId' value='afryca.consensusmodel.palomares2014cluster'/>
+      <property name='maven-version' value='1.0.0-SNAPSHOT'/>
+    </properties>
+    <provides size='6'>
+      <provided namespace='org.eclipse.equinox.p2.iu' name='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157'/>
+      <provided namespace='osgi.bundle' name='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157'/>
+      <provided namespace='osgi.identity' name='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157'>
+        <properties size='1'>
+          <property name='type' value='osgi.bundle'/>
+        </properties>
+      </provided>
+      <provided namespace='org.eclipse.equinox.p2.eclipse.type' name='bundle' version='1.0.0'/>
+      <provided namespace='org.eclipse.equinox.p2.localization' name='es' version='1.0.0'/>
+      <provided namespace='org.eclipse.equinox.p2.localization' name='df_LT' version='1.0.0'/>
+    </provides>
+    <requires size='2'>
+      <required namespace='osgi.bundle' name='afryca.consensusmodel' range='0.0.0'/>
+      <requiredProperties namespace='osgi.ee' match='(&amp;(osgi.ee=JavaSE)(version=1.8))'>
+        <description>
+          afryca.consensusmodel.palomares2014cluster
+        </description>
+      </requiredProperties>
+    </requires>
+    <artifacts size='1'>
+      <artifact classifier='osgi.bundle' id='afryca.consensusmodel.palomares2014cluster' version='1.0.0.202101221157'/>
+    </artifacts>
+    <touchpoint id='org.eclipse.equinox.p2.osgi' version='1.0.0'/>
+    <touchpointData size='1'>
+      <instructions size='1'>
+        <instruction key='manifest'>
+          Bundle-SymbolicName: afryca.consensusmodel.palomares2014cluster;singleton:=true&#xA;Bundle-Version: 1.0.0.202101221157&#xA;
+        </instruction>
+      </instructions>
+    </touchpointData>
+  </unit>
+</units>