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package com.dky.calculate;
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import com.dky.utils.entity.SysDeviceHeatScene;
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import com.dky.utils.result.MatchedDevice;
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import java.util.*;
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import java.util.concurrent.atomic.AtomicReference;
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public class SchemeRating {
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/**
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* 计算每一种方案的效率和成本评分
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* @param list
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* @return
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*/
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public static Map<Double, List<MatchedDevice>> getOptimalList(List<List<MatchedDevice>> list,Double costRatio,Double effRatio,Map<String,Double> maxEff,Map<String,Double> minPrice) {
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Map<Double, List<MatchedDevice>> optimalMap = new HashMap<>();
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list.forEach(plan->{
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AtomicReference<Double> rating = new AtomicReference<>(0.0);
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String devSubType = plan.get(0).getDeviceHeatScene().getDevSubType();
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Double eff = 0.0;
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Double cost = 0.0;
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for (MatchedDevice device : plan) {
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eff = device.getDeviceHeatScene().getHeatEfficiency();
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}
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for (MatchedDevice device : plan) {
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cost = cost + ((device.getCount() * device.getDeviceHeatScene().getDevPrice()) + (device.getCount()) * device.getDeviceHeatScene().getDevSubstituteLaborCost() * device.getDeviceHeatScene().getDevServiceLife());
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}
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//3、(1-(选择对应设备细类的效率最大的效率值(效率最大值)-当前设备的效率值值)/效率最大值)*100*系数 +(1-(当前成本值-对应设备细类的成本最小值)/对应设备细类的成本最小值)*100*0.2。取最高得分。
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rating.set(((1 - ((maxEff.get(devSubType) - eff) / maxEff.get(devSubType))) * 100 * effRatio) + ((1 - ((cost - minPrice.get(devSubType)) / minPrice.get(devSubType))) * 100 * costRatio));
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optimalMap.put(rating.get(), plan);
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});
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return optimalMap;
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}
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/**
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* 获取最优评分
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* @param map
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* @return
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*/
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public static List<MatchedDevice> getOptimalScheme(Map<Double, List<MatchedDevice>> map) {
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Set<Double> keySet = map.keySet();
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Double maxValue = keySet.iterator().next();
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for (Iterator<Double> iterator = keySet.iterator(); iterator.hasNext(); ) {
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Double value = iterator.next();
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if (value > maxValue) {
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maxValue = value;
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}
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}
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return map.get(maxValue);
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}
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/**
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* 获取不同设备细类下的效率最大值
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* @param alternateDeviceList 可替代设备列表
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* @return 不同设备细类下的效率最大值map
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*/
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public static Map<String,Double> getMaxEfficiencyGroupByDevSubType( List<SysDeviceHeatScene> alternateDeviceList){
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Map<String,Double> map = new HashMap<>();
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alternateDeviceList.forEach(alternateDevice ->{
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String devSubType = alternateDevice.getDevSubType();
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Double v = map.get(devSubType);
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if ( v == null){
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map.put(devSubType,alternateDevice.getHeatEfficiency());
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} else {
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if( alternateDevice.getHeatEfficiency() > v){
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map.put(devSubType,alternateDevice.getHeatEfficiency());
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}
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}
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});
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return map;
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}
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/**
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* 获取不同设备细类下的成本最小值
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* @param alternateDeviceList 可替代设备列表
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* @return 不同设备细类下的成本最小值map
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*/
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public static Map<String,Double> getMinPriceGroupByDevSubType( List<SysDeviceHeatScene> alternateDeviceList){
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Map<String,Double> map = new HashMap<>();
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alternateDeviceList.forEach(alternateDevice -> {
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String devSubType = alternateDevice.getDevSubType();
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Double v = map.get(devSubType);
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if ( v == null){
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map.put(devSubType,alternateDevice.getDevPrice()+ alternateDevice.getDevSubstituteLaborCost()*alternateDevice.getDevServiceLife());
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} else {
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if( alternateDevice.getDevPrice() < v){
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map.put(devSubType,alternateDevice.getDevPrice() + alternateDevice.getDevSubstituteLaborCost()*alternateDevice.getDevServiceLife());
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}
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}
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});
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return map;
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}
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public static List<Map<String, Double[]>> getIndex(List<List<MatchedDevice>> list) {
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List<Map<String, Double[]>> maps = new ArrayList<>();
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final Double[] index = {0.0, Double.MAX_VALUE};
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Map<String, Double[]> map = new HashMap<>();
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list.parallelStream().forEach((plan) -> {
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Double eff = 0.0;
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Double cost = 0.0;
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for (MatchedDevice device : plan) {
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eff = device.getDeviceHeatScene().getHeatEfficiency();
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}
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for (MatchedDevice device : plan) {
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cost = cost + ((device.getCount() * device.getDeviceHeatScene().getDevPrice()) + (device.getCount()) * device.getDeviceHeatScene().getDevSubstituteLaborCost() * device.getDeviceHeatScene().getDevServiceLife());
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}
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if (eff >= index[0]) {
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index[0] = eff;
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}
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if (cost <= index[1]) {
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index[1] = cost;
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}
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map.put(plan.get(0).getDeviceHeatScene().getDevSubType(), index);
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maps.add(map);
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});
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return maps;
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}
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}
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