Examples of rinde.sim.pdptw.gendreau06.Gendreau06ObjectiveFunction.computeCost()

Class rinde.sim.pdptw.gendreau06.Gendreau06ObjectiveFunction

Examples of rinde.sim.pdptw.gendreau06.Gendreau06ObjectiveFunction.computeCost()

rinde.sim.pdptw.gendreau06.Gendreau06ObjectiveFunction.computeCost()
Computes the cost according to the definition of the paper: the cost function used throughout this work is to minimize a weighted sum of three different criteria: total travel time, sum of lateness over all pick-up and delivery locations and sum of overtime over all vehicles. The function is defined as: sum(Tk) + alpha sum(max(0,tv-lv)) + beta sum(max(0,tk-l0)) Where: Tk is the total travel time on route Rk, alpha and beta are weighting parameters which were set to 1 in the paper. The definition of lateness: max(0,lateness) is commonly referred to as tardiness. All times are expressed in minutes.


      final GlobalStateObject solverInput = dsc.solver.getInputs().get(0);
      final ImmutableList<ImmutableList<ParcelDTO>> solverOutput = dsc.solver
          .getOutputs().get(0);


      assertEquals(obj.computeCost(results.results.get(0).stats),
          objValInMinutes, 0.2);


      final StatisticsDTO stats = Solvers.computeStats(solverInput,
          solverOutput);
      assertTrue(stats.toString(), obj.isValidResult(stats));

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          objValInMinutes, 0.2);


      final StatisticsDTO stats = Solvers.computeStats(solverInput,
          solverOutput);
      assertTrue(stats.toString(), obj.isValidResult(stats));
      assertEquals(objValInMinutes, obj.computeCost(stats), 0.1);
      assertEquals(objValInMinutes,
          decomposedCost(solverInput, solverOutput, obj), 0.01);
    }
  }

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      final double travelTime = obj.travelTime(stats);


      assertEquals(arrOverTime, obj.overTime(stats), 0.001);
      assertEquals(arrTravelTime, travelTime, 0.01);
      assertEquals(arrTardiness, tardiness, 0.001);
      assertEquals(arrObjVal, obj.computeCost(stats), 0.01);
      assertEquals(arrObjVal,
          decomposedCost(solverInput, solverOutput, obj), 0.01);
    }
  }

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        .add(ImmutableList.<ParcelDTO> of(d, d))
        .build();


    final StatisticsDTO stats = Solvers.computeStats(state, routes);
    final ObjectiveFunction objFunc = new Gendreau06ObjectiveFunction();
    final double cost = objFunc.computeCost(stats);


    final double cost0 = objFunc.computeCost(Solvers.computeStats(
        state.withSingleVehicle(0),
        ImmutableList.of(routes.get(0))));
    final double cost1 = objFunc.computeCost(Solvers.computeStats(

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    final StatisticsDTO stats = Solvers.computeStats(state, routes);
    final ObjectiveFunction objFunc = new Gendreau06ObjectiveFunction();
    final double cost = objFunc.computeCost(stats);


    final double cost0 = objFunc.computeCost(Solvers.computeStats(
        state.withSingleVehicle(0),
        ImmutableList.of(routes.get(0))));
    final double cost1 = objFunc.computeCost(Solvers.computeStats(
        state.withSingleVehicle(1),
        ImmutableList.of(routes.get(1))));

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    final double cost = objFunc.computeCost(stats);


    final double cost0 = objFunc.computeCost(Solvers.computeStats(
        state.withSingleVehicle(0),
        ImmutableList.of(routes.get(0))));
    final double cost1 = objFunc.computeCost(Solvers.computeStats(
        state.withSingleVehicle(1),
        ImmutableList.of(routes.get(1))));
    assertEquals(cost, cost0 + cost1, 0.001);
  }

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