using System;
using System.Linq;
using CommandLine;
using HeuristicLab.Data;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.Evolutionary;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.GRASP;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.LocalSearch;
using HeuristicLab.Problems.Instances.CordeauGQAP;

namespace GQAPSolver {
  public enum AlgorithmType { OSGA = 1, ILS = 2, ES = 3, GRASP = 4 }

  class CLOptions {
    [Value(0, HelpText = "Configuration ID, set by irace.")]
    public int ConfigId { get; set; }
    [Value(1, HelpText = "Instance ID, set by irace.")]
    public int InstanceId { get; set; }
    [Value(2, HelpText = "Seed, set by irace.")]
    public long Seed { get; set; }

    [Value(3, Default = "20-15-35", HelpText = "Name of the problem instance.", Required = true)]
    public string ProblemInstance { get; set; }

    [Option('a', "alg", Default = AlgorithmType.OSGA, HelpText = "Either: OSGA, ILS, ES, GRASP")]
    public AlgorithmType Algorithm { get; set; }

    [Option('t', "tries", Default = 1,
      HelpText = "Number of repetitions to perform.")]
    public int Tries { get; set; }
    [Option('r', "maxrt", Default = 60,
      HelpText = "Maximum runtime in seconds.")]
    public int MaxRuntime { get; set; }
    [Option('i', "maxiter", Default = 0,
      HelpText = "Maximum number of iterations.")]
    public int MaxIterations { get; set; }
    [Option('e', "maxeval", Default = 0,
      HelpText = "Maximum number of evaluations.")]
    public int MaxEvaluations { get; set; }

    [Option("popsize", Default = 500, HelpText = "Population size (OSGA)")]
    public int PopulationSize { get; set; }
    [Option("mutprob", Default = 0.05, HelpText = "Mutation probability (OSGA)")]
    public double MutationProbability { get; set; }

    [Option("pertstr", Default = 0.5, HelpText = "Perturbation strength (ILS)")]
    public double PerturbationStrength { get; set; }

    [Option("mu", Default = 10, HelpText = "Parent population size (ES)")]
    public int Mu { get; set; }
    [Option("lambda", Default = 10, HelpText = "Offspring population size (ES)")]
    public int Lambda { get; set; }
    [Option("evosel", Default = ESSelection.Plus, HelpText = "Selection strategy + or , (ES)")]
    public ESSelection Selection { get; set; }
    [Option("recomb", Default = 0, HelpText = "Use recombination 0 or 1 (ES)")]
    public int Recombination { get; set; }

    [Option("eliteset", Default = 10, HelpText = "Size of the elite set (GRASP)")]
    public int EliteSetSize { get; set; }
    [Option("mineliteset", Default = 2, HelpText = "Minimum size of the elite set (GRASP)")]
    public int MinimumEliteSetSize { get; set; }
    [Option("lsiters", Default = 100, HelpText = "Maximum local search iterations (GRASP)")]
    public int MaximumLocalSearchIterations { get; set; }
    [Option("candidatesize", Default = 0.5, HelpText = "Candidate Size Factor (GRASP)")]
    public double CandidateSizeFactor { get; set; }
    [Option("maxcandsize", Default = 10, HelpText = "Maximum candidate list size (GRASP)")]
    public int MaximumCandidateListSize { get; set; }
    [Option("onemoveprob", Default = 0.5, HelpText = "Probability for performing a 1-move (GRASP)")]
    public double OneMoveProbability { get; set; }
    [Option("mindiff", Default = 4, HelpText = "Minimum difference (GRASP)")]
    public int MinimumDifference { get; set; }
  }

  class Program {
    static void Main(string[] args) {
      var parsed = CommandLine.Parser.Default.ParseArguments<CLOptions>(args)
        .WithParsed(x => Run(x));
    }

    private static void Run(CLOptions opts) {
      var provider = new CordeauGQAPInstanceProvider();
      var descriptors = provider.GetDataDescriptors().ToList();
      var avgBest = 0.0;
      for (var t = 0; t < opts.Tries; t++) {
        HeuristicLab.Optimization.IAlgorithm alg = null;
        switch (opts.Algorithm) {
          case AlgorithmType.OSGA:
            alg = new OSGA() {
              MaximumEvaluations = opts.MaxEvaluations,
              MaximumIterations = opts.MaxIterations,
              MaximumRuntime = TimeSpan.FromSeconds(opts.MaxRuntime),
              PopulationSize = opts.PopulationSize,
              MutationProbability = opts.MutationProbability,
              StopAtBestKnownQuality = true,
              Seed = (int)opts.Seed,
              SetSeedRandomly = false
            };
            break;
          case AlgorithmType.ILS:
            alg = new IteratedLS() {
              MaximumEvaluations = opts.MaxEvaluations,
              MaximumIterations = opts.MaxIterations,
              MaximumRuntime = TimeSpan.FromSeconds(opts.MaxRuntime),
              PerturbationStrength = opts.PerturbationStrength,
              StopAtBestKnownQuality = true,
              Seed = (int)opts.Seed,
              SetSeedRandomly = false
            };
            break;
          case AlgorithmType.ES:
            alg = new EvolutionStrategy() {
              MaximumEvaluations = opts.MaxEvaluations,
              MaximumIterations = opts.MaxIterations,
              MaximumRuntime = TimeSpan.FromSeconds(opts.MaxRuntime),
              Mu = opts.Mu,
              Lambda = opts.Lambda,
              Selection = opts.Selection,
              UseRecombination = opts.Recombination > 0,
              StopAtBestKnownQuality = true,
              Seed = (int)opts.Seed,
              SetSeedRandomly = false
            };
            break;
          case AlgorithmType.GRASP:
            alg = new GRASP() {
              MaximumEvaluations = opts.MaxEvaluations,
              MaximumIterations = opts.MaxIterations,
              MaximumRuntime = TimeSpan.FromSeconds(opts.MaxRuntime),
              EliteSetSize = opts.EliteSetSize,
              MinimumEliteSetSize = opts.MinimumEliteSetSize,
              MaximumLocalSearchIterations = opts.MaximumLocalSearchIterations,
              CandidateSizeFactor = opts.CandidateSizeFactor,
              MaximumCandidateListSize = opts.MaximumCandidateListSize,
              OneMoveProbability = opts.OneMoveProbability,
              MinimumDifference = opts.MinimumDifference,
              StopAtBestKnownQuality = true,
              Seed = (int)opts.Seed,
              SetSeedRandomly = false
            };
            break;
        }
        if (alg == null) throw new InvalidOperationException("Unknown algorithm.");
        var prob = alg.Problem as GQAP;
        if (prob == null) alg.Problem = prob = new GQAP();
        prob.Load(provider.LoadData(descriptors.Single(x => x.Name == opts.ProblemInstance)));
        alg.Start();
        avgBest += ((DoubleValue)alg.Results["BestQuality"].Value).Value;
      }
      Console.WriteLine(avgBest / opts.Tries);
    }
  }
}