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Commit d07f3236 by yinyong
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供应链长度修改

parent 8dc25197
Showing with 159 additions and 118 deletions
data-show/show-auto-turnover/src/main/java/com/bailuntec/job/AutoTurnoverJob.java
...@@ -233,7 +233,15 @@ public class AutoTurnoverJob extends PointJob { ...@@ -233,7 +233,15 @@ public class AutoTurnoverJob extends PointJob {
* 所以预测2倍周转期长度 * 所以预测2倍周转期长度
* 2倍周转期长度 < 31 的, 默认算31天, 但是生成的采购建议不拿2倍周转期以外的 * 2倍周转期长度 < 31 的, 默认算31天, 但是生成的采购建议不拿2倍周转期以外的
*/ */
if (warehouseCode.equals(Constant.WAREHOUSE_JIT) && (turnoverSku.getBuyerName().equals(Constant.BUYER_JIT_1) || turnoverSku.getBuyerName().equals(Constant.BUYER_JIT_2) || turnoverSku.getBuyerName().equals(Constant.BUYER_JIT_3))) {
BigDecimal saveDays = getSaveDays(dcAutoSales, dcAutoTurnover, bailunSku, "autoForecastDay");
if(saveDays.compareTo(new BigDecimal(4)) > -1) {
saveDays = BigDecimal.valueOf(4);
}
turnoverDays = saveDays.intValue();
}
Integer autoForecastDay = turnoverDays * Constant.TURNOVER_MULTIPLE < Constant.MIN_AUTO_FORECAST_DAY ? Constant.MIN_AUTO_FORECAST_DAY : turnoverDays * 2; Integer autoForecastDay = turnoverDays * Constant.TURNOVER_MULTIPLE < Constant.MIN_AUTO_FORECAST_DAY ? Constant.MIN_AUTO_FORECAST_DAY : turnoverDays * 2;
/* /*
* 初始化预测容器, 用来存放预测销量, 库存等数据 * 初始化预测容器, 用来存放预测销量, 库存等数据
* forecastInventoryList * forecastInventoryList
...@@ -319,12 +327,33 @@ public class AutoTurnoverJob extends PointJob { ...@@ -319,12 +327,33 @@ public class AutoTurnoverJob extends PointJob {
//通过SKU和仓库拿到实际库存 //通过SKU和仓库拿到实际库存
Integer realInventory = (dcBaseStock != null && dcBaseStock.getUsableStock() != null) ? dcBaseStock.getUsableStock() : 0; Integer realInventory = (dcBaseStock != null && dcBaseStock.getUsableStock() != null) ? dcBaseStock.getUsableStock() : 0;
/*
* 通过SKU拿到供应商Id,
* 再去dc_average_purchase拿到平均交期
* 平均交期 - 供应商交期 > 0 就是平均逾期天数
*
* 平均逾期天数 * 加权平均销量(去最大值最小值)
* 为安全库存--即防止逾期缓冲所需库存
* 可以支持配置
* 2019-04-22更新 不管逾期
*/
BigDecimal totalSafeInventory = calculateSafeInventory( turnoverSku, bailunSku, warehouseCode, bailunFirstLevelCatagoryId, dcAutoSales, JSON.toJSONString(forecastSalesList), dcAutoTurnover);
Integer moq = turnoverSku.getMoq();
/*
* 预测库存 = 前一日库存 - 前一日销量(没有考虑实际缺货)
*
* 采购建议为周转期后那一天的销量 + 安全库存 - 预测库存 + 累计断货
* 如果有库存, 优先抵消断货数, 再去跟销量对比
*/
//通过SKU和仓库取预测销量
Integer inventoryAvailableDays = 0;
BigDecimal totalSales = BigDecimal.ZERO;//周转期总销量
BigDecimal totalInbound = BigDecimal.ZERO;//周转期总预计入库
BigDecimal moqDecimal = BigDecimal.valueOf(moq.longValue());
List<Integer> historySalesList = JSON.parseObject(dcAutoSales.getHistorySalesDetails(), new TypeReference<List<Integer>>() { List<Integer> historySalesList = JSON.parseObject(dcAutoSales.getHistorySalesDetails(), new TypeReference<List<Integer>>() {
}); });
/* /*
* dcAutoConfigSkuWarehouse不存在或者其status=0都是监控状态 * dcAutoConfigSkuWarehouse不存在或者其status=0都是监控状态
* 库存为0 并且 最近14天日均销量为0 * 库存为0 并且 最近14天日均销量为0
...@@ -353,32 +382,6 @@ public class AutoTurnoverJob extends PointJob { ...@@ -353,32 +382,6 @@ public class AutoTurnoverJob extends PointJob {
BigDecimal avgHistoryFourteendaySales = BigDecimal.valueOf(historyFourteenSales.longValue()).divide(Constant.BIGDECIMAL_FOURTEEN, 3, RoundingMode.HALF_EVEN); BigDecimal avgHistoryFourteendaySales = BigDecimal.valueOf(historyFourteenSales.longValue()).divide(Constant.BIGDECIMAL_FOURTEEN, 3, RoundingMode.HALF_EVEN);
BigDecimal avgHistoryThirtydaySales = BigDecimal.valueOf(historyThirtySales.longValue()).divide(Constant.BIGDECIMAL_THIRTY, 3, RoundingMode.HALF_EVEN); BigDecimal avgHistoryThirtydaySales = BigDecimal.valueOf(historyThirtySales.longValue()).divide(Constant.BIGDECIMAL_THIRTY, 3, RoundingMode.HALF_EVEN);
/*
* 通过SKU拿到供应商Id,
* 再去dc_average_purchase拿到平均交期
* 平均交期 - 供应商交期 > 0 就是平均逾期天数
*
* 平均逾期天数 * 加权平均销量(去最大值最小值)
* 为安全库存--即防止逾期缓冲所需库存
* 可以支持配置
* 2019-04-22更新 不管逾期
*/
BigDecimal totalSafeInventory = calculateSafeInventory(avgHistorySevendaySales, avgHistoryFourteendaySales, turnoverSku, bailunSku, warehouseCode, bailunFirstLevelCatagoryId, dcAutoSales, JSON.toJSONString(forecastSalesList), dcAutoTurnover);
Integer moq = turnoverSku.getMoq();
/*
* 预测库存 = 前一日库存 - 前一日销量(没有考虑实际缺货)
*
* 采购建议为周转期后那一天的销量 + 安全库存 - 预测库存 + 累计断货
* 如果有库存, 优先抵消断货数, 再去跟销量对比
*/
//通过SKU和仓库取预测销量
Integer inventoryAvailableDays = 0;
BigDecimal totalSales = BigDecimal.ZERO;//周转期总销量
BigDecimal totalInbound = BigDecimal.ZERO;//周转期总预计入库
BigDecimal moqDecimal = BigDecimal.valueOf(moq.longValue());
/* /*
* forecastFluctuationList 用于存放预计缺货 实际缺货 预计冗余 实际冗余的数据 * forecastFluctuationList 用于存放预计缺货 实际缺货 预计冗余 实际冗余的数据
* dcAutoConfigSkuWarehouse 看是否监控状态 * dcAutoConfigSkuWarehouse 看是否监控状态
...@@ -1082,7 +1085,7 @@ public class AutoTurnoverJob extends PointJob { ...@@ -1082,7 +1085,7 @@ public class AutoTurnoverJob extends PointJob {
} }
} }
private BigDecimal calculateSafeInventory(BigDecimal avgHistorySevendaySales, BigDecimal avgHistoryFourteendaySales, DcBaseSku turnoverSku, String bailunSku, String warehouseCode, Integer private BigDecimal calculateSafeInventory( DcBaseSku turnoverSku, String bailunSku, String warehouseCode, Integer
bailunFirstLevelCatagoryId, DcAutoSales dcAutoSales, String forecastSalesListJson, DcAutoTurnover dcAutoTurnover) { bailunFirstLevelCatagoryId, DcAutoSales dcAutoSales, String forecastSalesListJson, DcAutoTurnover dcAutoTurnover) {
/* /*
* 先判断是否JIT 仓库是广州01 warehouse_code 且是那三个销售员 turnoversku * 先判断是否JIT 仓库是广州01 warehouse_code 且是那三个销售员 turnoversku
...@@ -1092,95 +1095,8 @@ public class AutoTurnoverJob extends PointJob { ...@@ -1092,95 +1095,8 @@ public class AutoTurnoverJob extends PointJob {
List<BigDecimal> historyThirtySalesList = JSON.parseObject(dcAutoSales.getHistorySalesDetails(), new TypeReference<List<BigDecimal>>() { List<BigDecimal> historyThirtySalesList = JSON.parseObject(dcAutoSales.getHistorySalesDetails(), new TypeReference<List<BigDecimal>>() {
}); });
BigDecimal weightingAvgSales = caculateWeightingAvgSales(BigDecimal.valueOf(0.3), BigDecimal.valueOf(0.3), BigDecimal.valueOf(0.4), historyThirtySalesList); BigDecimal weightingAvgSales = caculateWeightingAvgSales(BigDecimal.valueOf(0.3), BigDecimal.valueOf(0.3), BigDecimal.valueOf(0.4), historyThirtySalesList);
DcAutoJitTagMapper dcAutoJitTagMapper = SessionUtil.getSession().getMapper(DcAutoJitTagMapper.class);
List<DcAutoJitTag> dcAutoJitTags = dcAutoJitTagMapper.selectByExample(DcAutoJitTagExample.newAndCreateCriteria().example()); BigDecimal saveDays = getSaveDays(dcAutoSales, dcAutoTurnover, bailunSku, "weightingAvgSales");
BigDecimal saveDays = BigDecimal.ZERO;
for(DcAutoJitTag dcAutoJitTag : dcAutoJitTags) {
if(dcAutoJitTag.getEnable7() == 1) {
switch (dcAutoJitTag.getIsGt7()){
case 1:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == 1) {
break;
}else {
continue;
}
case 2:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == 0) {
break;
}else {
continue;
}
case 3:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == -1) {
break;
}else {
continue;
}
case 4:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) > -1) {
break;
}else {
continue;
}
case 5:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) < 1) {
break;
}else {
continue;
}
default:
continue;
}
}
if(dcAutoJitTag.getEnable14() == 1) {
switch (dcAutoJitTag.getIsGt14()){
case 1:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == 1) {
break;
}else {
continue;
}
case 2:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == 0) {
break;
}else {
continue;
}
case 3:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == -1) {
break;
}else {
continue;
}
case 4:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) > -1) {
break;
}else {
continue;
}
case 5:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) < 1) {
break;
}else {
continue;
}
default:
continue;
}
}
saveDays = dcAutoJitTag.getQuantitySafeInventory();
DcAutoJitTagLogMapper dcAutoJitTagLogMapper = SessionUtil.getSession().getMapper(DcAutoJitTagLogMapper.class);
DcAutoJitTagLog dcAutoJitTagLog = new DcAutoJitTagLog();
dcAutoJitTagLog.setBailunSku(bailunSku);
dcAutoJitTagLog.setDate(LocalDate.now());
dcAutoJitTagLog.setQuantitySales7(avgHistorySevendaySales);
dcAutoJitTagLog.setQuantitySales14(avgHistoryFourteendaySales);
dcAutoJitTagLog.setTagId(dcAutoJitTag.getId());
dcAutoJitTagLog.setTagJson(JSONObject.toJSONString(dcAutoJitTag));
dcAutoJitTagLogMapper.upsertSelective(dcAutoJitTagLog);
dcAutoTurnover.setTagId(dcAutoJitTag.getId());
break;
}
dcAutoTurnover.setDailyWeightedSales(weightingAvgSales); dcAutoTurnover.setDailyWeightedSales(weightingAvgSales);
weightingAvgSales = weightingAvgSales.multiply(saveDays); weightingAvgSales = weightingAvgSales.multiply(saveDays);
return weightingAvgSales; return weightingAvgSales;
...@@ -1881,4 +1797,129 @@ public class AutoTurnoverJob extends PointJob { ...@@ -1881,4 +1797,129 @@ public class AutoTurnoverJob extends PointJob {
} }
return (int) totalPage; return (int) totalPage;
} }
public BigDecimal getSaveDays(DcAutoSales dcAutoSales, DcAutoTurnover dcAutoTurnover, String bailunSku, String autoForecastDay) {
List<Integer> historySalesList = JSON.parseObject(dcAutoSales.getHistorySalesDetails(), new TypeReference<List<Integer>>() {
});
/*
* dcAutoConfigSkuWarehouse不存在或者其status=0都是监控状态
* 库存为0 并且 最近14天日均销量为0
* 已经提醒实际缺货的，预计缺货就不提醒了
* 已经提醒实际冗余的，预计冗余就不提醒了
* 停止监控的不提醒
*/
Integer historyFourteenSales = 0;
Integer historySevenSales = 0;
Integer historyThreeSales = 0;
Integer historyThirtySales = 0;
for (int i = 0; i < 30; i++) {
if (i < 3) {
historyThreeSales += historySalesList.get(27 + i);
}
if (i < 7) {
historySevenSales += historySalesList.get(23 + i);
}
if (i < 14) {
historyFourteenSales += historySalesList.get(16 + i);
}
historyThirtySales += historySalesList.get(i);
}
BigDecimal avgHistoryThreedaySales = BigDecimal.valueOf(historyThreeSales.longValue()).divide(Constant.BIGDECIMAL_THREE, 3, RoundingMode.HALF_EVEN);
BigDecimal avgHistorySevendaySales = BigDecimal.valueOf(historySevenSales.longValue()).divide(Constant.BIGDECIMAL_SEVEN, 3, RoundingMode.HALF_EVEN);
BigDecimal avgHistoryFourteendaySales = BigDecimal.valueOf(historyFourteenSales.longValue()).divide(Constant.BIGDECIMAL_FOURTEEN, 3, RoundingMode.HALF_EVEN);
BigDecimal avgHistoryThirtydaySales = BigDecimal.valueOf(historyThirtySales.longValue()).divide(Constant.BIGDECIMAL_THIRTY, 3, RoundingMode.HALF_EVEN);
DcAutoJitTagMapper dcAutoJitTagMapper = SessionUtil.getSession().getMapper(DcAutoJitTagMapper.class);
List<DcAutoJitTag> dcAutoJitTags = dcAutoJitTagMapper.selectByExample(DcAutoJitTagExample.newAndCreateCriteria().example());
BigDecimal saveDays = BigDecimal.ZERO;
for(DcAutoJitTag dcAutoJitTag : dcAutoJitTags) {
if(dcAutoJitTag.getEnable7() == 1) {
switch (dcAutoJitTag.getIsGt7()){
case 1:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == 1) {
break;
}else {
continue;
}
case 2:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == 0) {
break;
}else {
continue;
}
case 3:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) == -1) {
break;
}else {
continue;
}
case 4:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) > -1) {
break;
}else {
continue;
}
case 5:
if(avgHistorySevendaySales.compareTo(dcAutoJitTag.getQuantitySales7()) < 1) {
break;
}else {
continue;
}
default:
continue;
}
}
if(dcAutoJitTag.getEnable14() == 1) {
switch (dcAutoJitTag.getIsGt14()){
case 1:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == 1) {
break;
}else {
continue;
}
case 2:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == 0) {
break;
}else {
continue;
}
case 3:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) == -1) {
break;
}else {
continue;
}
case 4:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) > -1) {
break;
}else {
continue;
}
case 5:
if(avgHistoryFourteendaySales.compareTo(dcAutoJitTag.getQuantitySales14()) < 1) {
break;
}else {
continue;
}
default:
continue;
}
}
saveDays = dcAutoJitTag.getQuantitySafeInventory();
if("weightingAvgSales".equals(autoForecastDay)) {
DcAutoJitTagLogMapper dcAutoJitTagLogMapper = SessionUtil.getSession().getMapper(DcAutoJitTagLogMapper.class);
DcAutoJitTagLog dcAutoJitTagLog = new DcAutoJitTagLog();
dcAutoJitTagLog.setBailunSku(bailunSku);
dcAutoJitTagLog.setDate(LocalDate.now());
dcAutoJitTagLog.setQuantitySales7(avgHistorySevendaySales);
dcAutoJitTagLog.setQuantitySales14(avgHistoryFourteendaySales);
dcAutoJitTagLog.setTagId(dcAutoJitTag.getId());
dcAutoJitTagLog.setTagJson(JSONObject.toJSONString(dcAutoJitTag));
dcAutoJitTagLogMapper.upsertSelective(dcAutoJitTagLog);
dcAutoTurnover.setTagId(dcAutoJitTag.getId());
}
break;
}
return saveDays;
}
} }
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