dntd-model-tools/dntd-model-buildheating/src/main/java/com/dky/calculate/SchemeRating.java

package com.dky.calculate;


import com.dky.utils.result.MatchedDevice;

import java.util.*;
import java.util.concurrent.atomic.AtomicReference;

public class SchemeRating {

    /**
     * 计算效率和成本评分
     * @param list
     * @return
     */
    public static Map<Double, List<MatchedDevice>> getOptimalList(List<Map<String, List<List<MatchedDevice>>>> list,Double costRatio,Double effRatio) {
        Map<Double, List<MatchedDevice>> optimalMap = new HashMap<>();
        list.parallelStream().forEach(stringListMap -> {
            // 区分热泵、电锅炉
            stringListMap.forEach((k,v)->{
                // 循环遍历各个方案
                v.parallelStream().forEach((plan)->{
                    AtomicReference<Double> rating = new AtomicReference<>(0.0);
                    List<Map<String, Double[]>> maps = getIndex(list);
                    for (Map<String, Double[]> map : maps) {
                        map.forEach((k1, v1) -> {
                            if (k1.equals(k)){
                                Double eff = 0.0;
                                Double cost = 0.0;
                                for (MatchedDevice device : plan) {
                                    eff = device.getDeviceHeatScene().getHeatEfficiency();
                                }
                                for (MatchedDevice device : plan) {
                                    cost = cost + ((device.getCount() * device.getDeviceHeatScene().getDevPrice()) + (device.getCount()) * device.getDeviceHeatScene().getDevSubstituteLaborCost() * device.getDeviceHeatScene().getDevServiceLife());
                                }
                                //3、效率成本公式：（1-（选择效率最大-当前值）/效率最大值）*100*0.8  +（1-（当前值-选择成本最小）/成本最小值）*100*0.2。
                                rating.set(((1 - ((v1[0] - eff) / v1[0])) * 100 * effRatio) + ((1 - ((cost - v1[1]) / v1[1])) * 100 * costRatio));
                                optimalMap.put(rating.get(), plan);
                            }
                        });
                    }
                });
            });
        });
        return optimalMap;
    }

    /**
     * 获取最优评分
     * @param map
     * @return
     */
    public static List<MatchedDevice> getOptimalScheme(Map<Double, List<MatchedDevice>> map) {
        Set<Double> keySet = map.keySet();
        Double maxValue = keySet.iterator().next();
        for (Iterator<Double> iterator = keySet.iterator(); iterator.hasNext(); ) {
            Double value = iterator.next();
            if (value > maxValue) {
                maxValue = value;
            }
        }
        return map.get(maxValue);
    }

    public static List<Map<String, Double[]>> getIndex(List<Map<String, List<List<MatchedDevice>>>> list) {
        List<Map<String, Double[]>> maps = new ArrayList<>();
        list.parallelStream().forEach(stringListMap -> {
            // 区分热泵、电锅炉
            stringListMap.forEach((k, v) -> {
                // 循环遍历各个方案
                // 热效率、成本
                final Double[] index = {0.0, Double.MAX_VALUE};
                v.parallelStream().forEach((plan) -> {
                    Double eff = 0.0;
                    Double cost = 0.0;
                    for (MatchedDevice device : plan) {
                        eff = device.getDeviceHeatScene().getHeatEfficiency();
                    }
                    for (MatchedDevice device : plan) {
                        cost = cost + ((device.getCount() * device.getDeviceHeatScene().getDevPrice()) + (device.getCount()) * device.getDeviceHeatScene().getDevSubstituteLaborCost() * device.getDeviceHeatScene().getDevServiceLife());
                    }
                    if (eff >= index[0]) {
                        index[0] = eff;
                    }
                    if (cost <= index[1]) {
                        index[1] = cost;
                    }
                });
                Map<String, Double[]> map = new HashMap<>();
                map.put(k, index);
                maps.add(map);
            });
        });

        return maps;
    }




}