Пример #1
0
 private Double getWeight1(long age) {
   // Weight that will be used when status_cd = ACTIVE
   if (age <= 0) {
     return SystemDao.getDefaultWeight();
   }
   return Math.max(0.2, 1.0 / age);
 }
Пример #2
0
  private void performDailyLearning() {
    updateStatusCode();
    if (statusCd != STATUS_CD.LEARNING || disableLearning == true) {
      return;
    }
    if (onRange && (rcBopInv > 0 || hasSale == true || rcInvIn > 0)) {
      initLearningMetrics();
      // Daily learning only applies to RC_AVG_DEMAND and begins immediately when the PL comes on
      // range
      double lastWeekLift = getDemandUplift(SystemDao.getReviewCycleStartDate());
      double defaultWeight = SystemDao.getDefaultWeight();
      Demand beginOfRunCycleDemand = getDemand(SystemDao.getReviewCycleStartDate());
      double beginOfRunCycleRcAvgDemand = 0;
      if (beginOfRunCycleDemand != null) {
        beginOfRunCycleRcAvgDemand = beginOfRunCycleDemand.getRcAvgDemand();
      }

      if (onRange && !disableLearning) {
        rcAvgDemand =
            getWeightedWeight1(learningWeekCounter, defaultWeight) * rcDemand / lastWeekLift
                + (1 - getWeightedWeight1(learningWeekCounter, defaultWeight))
                    * beginOfRunCycleRcAvgDemand;
      }
    }
  }
Пример #3
0
  private void initLearningMetrics() {
    if (learningMetricsInitialized) {
      return;
    }
    double defaultWeight = SystemDao.getDefaultWeight();
    double lastWeekLift = getDemandUplift(SystemDao.getReviewCycleStartDate());
    Sales beginOfRunCycleSales = getSales(SystemDao.getReviewCycleStartDate());
    double beginOfRunCycleRcAvgSales = 0;
    if (beginOfRunCycleSales != null) {
      beginOfRunCycleRcAvgSales = beginOfRunCycleSales.getRcAvgSales();
    }

    rcAvgSales =
        getWeightedWeight1(learningWeekCounter, defaultWeight) * epSales / lastWeekLift
            + (1 - getWeightedWeight1(learningWeekCounter, defaultWeight))
                * beginOfRunCycleRcAvgSales;

    // Tim's documentation states:
    // Its important sales metrics are initialized to AVG_WEEKLY_SALES based on the initialization
    // logic.
    // This estimates initial values based on different combinations of the PLs product and location
    // hierarchies dependent on the specific situation for that PL
    rcAvgSalesActual = rcAvgSales;
    rcAvgDemand = rcAvgSales;
    rcOldAvgDemand = rcAvgSales;
    rcAvgDemandActual = rcAvgSales;
    epAvgInv = rcAvgSales;
    rcWass2 = Math.pow(rcAvgSales, 2);
    learningMetricsInitialized = true;
  }
Пример #4
0
  private void processWeeklyMetrics() {
    // On the end of the review cycle (Sat night) the rcAvgDemand does not undergo weekly learning
    // For this exercise we do not have time granulity  so weekly processing is done Sunday for the
    // prior week

    LocalDate crc = SystemDao.getCrc();
    LocalDate prevCRCStartDate = SystemDao.getReviewCycleStartDate(); // getPreviousCRCStartDate();
    Sales salesData = getSales(crc);

    Sales beginOfPeriodSalesData = getSales(prevCRCStartDate);
    double beginOfPeriodRcAvgSales = 0;
    double beginOfPeriodRcActualAvgSales = 0;
    if (beginOfPeriodSalesData != null) {
      beginOfPeriodRcAvgSales = beginOfPeriodSalesData.getRcAvgSales();
      beginOfPeriodRcActualAvgSales = beginOfPeriodSalesData.getRcAvgSalesActual();
    }

    Demand demandData = getDemand(crc);
    Demand beginOfPeriodDemandData = getDemand(prevCRCStartDate);
    double beginOfPeriodRcAvgDemand = 0;
    double beginOfPeriodRcAvgActualDemand = 0;
    if (beginOfPeriodDemandData != null) {
      beginOfPeriodRcAvgDemand = beginOfPeriodDemandData.getRcAvgDemand();
      beginOfPeriodRcAvgActualDemand = beginOfPeriodDemandData.getRcAvgDemandActual();
    }
    double defaultWeight = SystemDao.getDefaultWeight();

    double lastWeekLift = getDemandUplift(prevCRCStartDate);
    double weight = 1.0;
    if (statusCd == STATUS_CD.LEARNING) {
      weight = getWeightedWeight1(learningWeekCounter, defaultWeight);
    } else if (statusCd == STATUS_CD.ACTIVE) {
      weight = getWeight1(learningWeekCounter);
    }

    rcAvgSalesActual =
        (weight * (salesData.getRcSalesActual() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcActualAvgSales);
    rcAvgSales =
        (weight * (salesData.getRcSales() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgSales);
    rcAvgDemand =
        (weight * (demandData.getRcDemand() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgDemand);
    rcAvgDemandActual =
        (weight * (demandData.getRcDemandActual() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgActualDemand);

    // error checking
    if (rcAvgDemand == 0 && statusCd != STATUS_CD.INACTIVE) {
      System.out.println("Error: 0 demand when product status is not inactive");
    }
    if (rcAvgDemand >= 4 * rcAvgSales) {
      rcAvgSales = 4 * rcAvgSalesActual;
      System.out.println("Error: RC Actual Sales greater then 4 times RC Average Sales");
    }
    if (rcAvgDemand >= 3 * rcAvgSalesActual) {
      rcAvgSales = 3 * rcAvgSalesActual;
      System.out.println("Error: RC Actual Sales greater then 3 times RC Actual Average Sales");
    }

    storeWeeklyMetrics(crc);
    this.learningWeekCounter++;
    // this is the end of the review cycle reset hasBeenOffRange
    if (hasBeenOffRange) {
      hasBeenOffRange = false;
    }
    resetRcAccumulators();
  }