namespace PBS.Console.Test
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{
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using System;
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using System.Collections.Generic;
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public class WaterDistributionSystem1
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{
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#region 核心算法类
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public class ModelConfig
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{
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public int NodeCount { get; set; } // 节点总数
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public int TotalRuns { get; set; } // 总计算次数
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public double MinDemand { get; set; } // 最小总需水量(m³/h)
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public double MaxDemand { get; set; } // 最大总需水量(m³/h)
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public List<(double min, double max)> NodeLimits { get; set; } = new(); // 节点水量限制
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}
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public class SimulationResult
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{
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public double TotalDemand { get; set; }
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public double[] NodeDemands { get; }
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public DateTime Timestamp { get; }
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public SimulationResult(int nodeCount)
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{
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NodeDemands = new double[nodeCount];
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Timestamp = DateTime.Now;
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}
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}
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public class DemandGenerator
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{
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private readonly ModelConfig _config;
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private readonly Random _rand = new();
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public DemandGenerator(ModelConfig config) => _config = config;
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// 生成需求矩阵（符合规范[6](@ref)的线性递增策略）
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public List<SimulationResult> GenerateDemandMatrix()
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{
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var results = new List<SimulationResult>(_config.TotalRuns);
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double step = (_config.MaxDemand - _config.MinDemand) / (_config.TotalRuns - 1);
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for (int i = 0; i < _config.TotalRuns; i++)
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{
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double currentDemand = _config.MinDemand + step * i;
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results.Add(GenerateDemandSet(currentDemand));
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}
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return results;
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}
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// 单个需求集生成算法（包含节点约束[4](@ref)）
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private SimulationResult GenerateDemandSet(double totalDemand)
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{
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var result = new SimulationResult(_config.NodeCount);
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double remaining = totalDemand;
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// 第一阶段：分配最小需求
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for (int i = 0; i < _config.NodeCount; i++)
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{
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result.NodeDemands[i] = _config.NodeLimits[i].min;
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remaining -= result.NodeDemands[i];
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}
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// 第二阶段：加权随机分配剩余水量（遗传算法优化思路[1](@ref)）
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double[] weights = GenerateWeights();
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double weightSum = Sum(weights);
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for (int i = 0; i < _config.NodeCount && remaining > 0; i++)
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{
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double allocatable = Math.Min(
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remaining * (weights[i] / weightSum),
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_config.NodeLimits[i].max - result.NodeDemands[i]
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);
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result.NodeDemands[i] += allocatable;
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remaining -= allocatable;
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}
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// 第三阶段：误差修正（确保总和精确）
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if (remaining > 0)
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{
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int index = _rand.Next(_config.NodeCount);
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result.NodeDemands[index] = Math.Min(
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result.NodeDemands[index] + remaining,
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_config.NodeLimits[index].max
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);
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}
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result.TotalDemand = Sum(result.NodeDemands);
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return result;
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}
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// 生成遗传算法权重（参考[1,3](@ref)）
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private double[] GenerateWeights()
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{
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double[] weights = new double[_config.NodeCount];
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for (int i = 0; i < weights.Length; i++)
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{
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weights[i] = _rand.NextDouble() * 0.8 + 0.2; // 20%基础权重+随机变异
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}
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return weights;
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}
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private static double Sum(double[] arr)
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{
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double sum = 0;
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foreach (var v in arr) sum += v;
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return sum;
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}
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}
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#endregion
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//#region 使用示例
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//public static void Main()
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//{
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// var config = new ModelConfig
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// {
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// NodeCount = 5,
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// TotalRuns = 10,
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// MinDemand = 50,
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// MaxDemand = 500,
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// NodeLimits = new List<(double, double)> {
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// (0, 100), (10, 150), (5, 80), (20, 200), (0, 120)
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// }
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// };
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// var generator = new DemandGenerator(config);
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// var results = generator.GenerateDemandMatrix();
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// // 输出验证
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// foreach (var r in results)
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// {
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// Console.WriteLine($"Total: {r.TotalDemand:F2} | Nodes: {string.Join(", ", r.NodeDemands)}");
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// }
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//}
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//#endregion
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}
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public class WaterDistributionSystemHelper
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{
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public class Config
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{
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public int NodeCount { get; set; } // 节点总数
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public int TotalRuns { get; set; } // 计算次数
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public double MinDemand { get; set; } // 最小总需水量(m³/h)
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public double MaxDemand { get; set; } // 最大总需水量(m³/h)
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public List<(double min, double max)> NodeLimits { get; set; } = new(); // 节点水量限制
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}
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public class AllocationResult
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{
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public double TotalDemand { get; set; }
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public double[] NodeDemands { get; }
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public DateTime Timestamp { get; }
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public AllocationResult(int nodeCount)
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{
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NodeDemands = new double[nodeCount];
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Timestamp = DateTime.Now;
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}
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}
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public class DemandAllocator
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{
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private readonly Config _config;
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private readonly Random _rand = new();
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public DemandAllocator(Config config)
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{
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ValidateConfig(config);
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_config = config;
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}
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public List<AllocationResult> GenerateAllocationMatrix()
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{
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var results = new List<AllocationResult>(_config.TotalRuns);
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double step = (_config.MaxDemand - _config.MinDemand) / (_config.TotalRuns - 1);
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// 根据GB50015规范考虑未预见水量[6](@ref)
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for (int i = 0; i < _config.TotalRuns; i++)
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{
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double currentDemand = _config.MinDemand + step * i;
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results.Add(GenerateAllocation(currentDemand));
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}
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return results;
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}
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private AllocationResult GenerateAllocation(double totalDemand)
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{
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var result = new AllocationResult(_config.NodeCount);
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double remaining = totalDemand;
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// 第一阶段：分配最低需水量（符合设计秒流量规范[7](@ref)）
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for (int i = 0; i < _config.NodeCount; i++)
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{
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result.NodeDemands[i] = _config.NodeLimits[i].min;
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remaining -= result.NodeDemands[i];
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}
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// 第二阶段：遗传算法式加权分配（参考专利[5](@ref)）
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double[] weights = GenerateGeneticWeights();
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double weightSum = Sum(weights);
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for (int i = 0; i < _config.NodeCount && remaining > 0; i++)
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{
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double allocatable = Math.Min(
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remaining * (weights[i] / weightSum),
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_config.NodeLimits[i].max - result.NodeDemands[i]
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);
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result.NodeDemands[i] += allocatable;
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remaining -= allocatable;
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}
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// 第三阶段：误差修正（确保总和精确）
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if (remaining > 0)
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{
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int index = _rand.Next(_config.NodeCount);
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result.NodeDemands[index] = Math.Min(
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result.NodeDemands[index] + remaining,
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_config.NodeLimits[index].max
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);
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}
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result.TotalDemand = Sum(result.NodeDemands);
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return result;
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}
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// 遗传算法权重生成（20%基础权重+随机变异[3](@ref)）
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private double[] GenerateGeneticWeights()
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{
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double[] weights = new double[_config.NodeCount];
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for (int i = 0; i < weights.Length; i++)
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{
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weights[i] = _rand.NextDouble() * 0.8 + 0.2;
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}
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return weights;
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}
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private static double Sum(double[] arr)
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{
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double sum = 0;
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foreach (var v in arr) sum += v;
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return sum;
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}
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private void ValidateConfig(Config config)
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{
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double totalMin = 0;
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foreach (var limit in config.NodeLimits)
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{
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totalMin += limit.min;
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if (limit.min < 0 || limit.max < limit.min)
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throw new ArgumentException("节点限制值无效");
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}
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if (totalMin > config.MaxDemand)
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throw new ArgumentException("总最小需求超过最大设定值");
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}
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}
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}
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}
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