Example #1
0
        public FSPSolution GenerateNeighbor(TabuMemory explicitLocalTabuMemory)
        {
            var copyCurrentSolution = new FSPSolution(this);
            var selectedPhrases     = copyCurrentSolution.ObtainSelectedPhrasesSortedByCoverageCosine();

            // Remove the last sentence (phrases with low coverage) ... C = 1
            copyCurrentSolution.InActivate(selectedPhrases[selectedPhrases.Count - 1].Position);
            var excludePhrases = new List <int> {
                selectedPhrases[selectedPhrases.Count - 1].Position
            };

            var         tries                = 0;
            const int   maxTries             = 5;
            FSPSolution newCandidateSolution = null;

            do
            {
                newCandidateSolution = new FSPSolution(copyCurrentSolution);
                // Try to add one or more randomly selected phrases to complete the solution
                newCandidateSolution.AddValidPhrases(excludePhrases);
                if (tries++ < maxTries)
                {
                    break;                     // avoid long time in the loop
                }
            } while (explicitLocalTabuMemory.IsTabu(newCandidateSolution.SelectedPhrases));
            newCandidateSolution.CalculateFitness();

            return(newCandidateSolution);
        }
Example #2
0
        public List <PositionValue> Execute()
        {
            CurrentFFEs = 0;
            var myParameters = (SFLAParameters)MyParameters;

            // Setup of Memeplexes
            Memeplex = new List <Frog> [myParameters.NumberOfMemeplexes];
            for (var i = 0; i < myParameters.NumberOfMemeplexes; i++)
            {
                Memeplex[i] = new List <Frog>();
            }
            FrogsByMemeplex = myParameters.PondSize / myParameters.NumberOfMemeplexes;

            // Calculate the ranking of the position of the phrases
            CalculateRankingPhrasePosition();

            // Tabu memory of the specified type is created with the desired amount
            MyTabuMemory = new TabuMemory(myParameters.Tenure);

            // Initialize the Pond with frogs
            Pond = new List <Frog>();
            while (Pond.Count < myParameters.PondSize)
            {
                var frog = new Frog(this);
                frog.RandomInitialization();
                if (MyTabuMemory.IsTabu(frog.SelectedPhrases))
                {
                    continue;
                }
                Pond.Add(frog);
                MyTabuMemory.Include(frog.SelectedPhrases);
            }

            Pond.Sort((x, y) => - 1 * x.Fitness.CompareTo(y.Fitness));
            GBest = new Frog(Pond[0]);

            while (CurrentFFEs < MaximumNumberOfFitnessFunctionEvaluations)
            {
                ShuffletheFrogs();
                LocalSearch();
                RegroupTheFrogs();
                MutateTheFrogs();

                Pond.Sort((x, y) => - 1 * x.Fitness.CompareTo(y.Fitness));
                GBest = new Frog(Pond[0]);
            }
            var mostRepeated = SelectToCompleteSummary(
                new List <BaseSolution>(Pond), GBest);
            var listaFrases = SelectPhrasesFromFinalSummary(
                GBest.SelectedPhrases, mostRepeated);

            return(listaFrases);
        }
Example #3
0
        private void LocalSearch()
        {
            var myParameters = (SFLAParameters)MyParameters;

            for (var mplex = 0; mplex < myParameters.NumberOfMemeplexes; mplex++)
            {
                if (CurrentFFEs > MaximumNumberOfFitnessFunctionEvaluations)
                {
                    break;
                }

                for (var iteration = 0; iteration < myParameters.MaxLocalIterations; iteration++)
                {
                    if (CurrentFFEs > MaximumNumberOfFitnessFunctionEvaluations)
                    {
                        break;
                    }

                    var bestFrog  = new Frog((Memeplex[mplex])[0]);
                    var worstFrog = new Frog((Memeplex[mplex])[FrogsByMemeplex - 1]);

                    var auxiliarFrog = new Frog(worstFrog);
                    auxiliarFrog.Jump(bestFrog);
                    if (MyTabuMemory.IsTabu(auxiliarFrog.SelectedPhrases))
                    {
                        auxiliarFrog.Fitness = 0;
                    }

                    if (auxiliarFrog.Fitness > worstFrog.Fitness)
                    {
                        (Memeplex[mplex])[FrogsByMemeplex - 1] = auxiliarFrog;
                    }
                    else
                    {
                        auxiliarFrog = new Frog(worstFrog);
                        auxiliarFrog.Jump(GBest);
                        if (MyTabuMemory.IsTabu(auxiliarFrog.SelectedPhrases))
                        {
                            auxiliarFrog.Fitness = 0;
                        }

                        if (auxiliarFrog.Fitness > worstFrog.Fitness)
                        {
                            (Memeplex[mplex])[FrogsByMemeplex - 1] = auxiliarFrog;
                        }
                        else
                        {
                            auxiliarFrog = new Frog(this);
                            auxiliarFrog.RandomInitialization();
                            if (!MyTabuMemory.IsTabu(auxiliarFrog.SelectedPhrases))
                            {
                                (Memeplex[mplex])[FrogsByMemeplex - 1] = auxiliarFrog;
                            }
                        }
                    }
                    if (auxiliarFrog.Fitness > GBest.Fitness)
                    {
                        GBest = new Frog(auxiliarFrog);
                    }
                }
                Memeplex[mplex].Sort((x, y) => - 1 * x.Fitness.CompareTo(y.Fitness));
            }
        }