public Reporte(Simplex sollutions)
{
_sollutions = sollutions;
SimplexSolverParams solverParams = new SimplexSolverParams();
solverParams.GetSensitivityReport = true;
_sollutions.Solver.Solve(solverParams);
_reportSensitivity = _sollutions.Solver.GetReport(LinearSolverReportType.Sensitivity);
_sensitivityReport = _reportSensitivity as ILinearSolverSensitivityReport;
}
public void Get()
{
SimplexSolver solver = new SimplexSolver();
double[] estimatedProfitOfProjectX = new double[] { 1, 1.8, 1.6, 0.8, 1.4 };
double[] capitalRequiredForProjectX = new double[] { 6, 12, 10, 4, 8 };
double availableCapital = 20;
int[] chooseProjectX = new int[5];
int profit;
solver.AddRow("profit", out profit);
solver.AddGoal(profit, 0, false);
int expenditure;
solver.AddRow("expenditure", out expenditure);
solver.SetBounds(expenditure, 0, availableCapital);
for (int i = 0; i < 5; i++)
{
solver.AddVariable(string.Format("project{0}", i), out chooseProjectX[i]);
solver.SetBounds(chooseProjectX[i], 0, 1);
solver.SetIntegrality(chooseProjectX[i], true);
solver.SetCoefficient(profit, chooseProjectX[i], estimatedProfitOfProjectX[i]);
solver.SetCoefficient(expenditure, chooseProjectX[i], capitalRequiredForProjectX[i]);
}
SimplexSolverParams param = new SimplexSolverParams();
param.MixedIntegerGenerateCuts = true;
solver.Solve(param);
Console.WriteLine(solver.MipResult);
for (int i = 0; i < 5; i++)
{
Console.WriteLine("Project {0} is {1} selected.", i, solver.GetValue(chooseProjectX[i]) == 1 ? "" : "not ");
}
Console.WriteLine("The estimated total profit is: ${0} million.", (double)solver.GetValue(profit).ToDouble());
Console.WriteLine("The total expenditure is: ${0} million.", solver.GetValue(expenditure).ToDouble());
}
/// <summary>
/// Solves a sample (randomly generated?) cutting stock problem.
/// Given a bolt of cloth of fixed width, and demand for cut strips of the cloth, determine the min "loss" cut patterns to use and how many
/// of them.
/// Loss is defined as the scrap thrown away.
/// It is acceptable to have extra cut widths made. They do not contribute to the cost. (this may be unrealistic in the real world)
/// Solver runs by 1st creating an enumeration of possible cut patterns using a CspSolver, then choosing between the patterns and selecting a qty of the patterns such that the
/// amount of scrap is minimized and all demand is met using the SimplexSolver MIP code.
///
/// In an industrial case, there would likely be more constraints in the generation of the cut patterns. There can be other restrictions such as "these can't be done together"
/// or "these MUST be done together (matching pattern or color?)". This can easily be added to the CspSolver model.
/// Also, there are likely other characteristics of the cuts or the master problem which would need adaptations.
///
/// Further, the limit on the columns generated is implemented in a very arbitrary order. It is more likely that some ordering of the
/// value of the columns is needed. In most industrial occurances, the dual variables from the LP relaxation would likely be used to
/// guide the generation of columns in an interative fasion rather than a one-time shot at the beginning.
///
/// YMMV
/// </summary>
public static void ShortCuttingStock()
{
Console.WriteLine("*** Short Cutting Stock ***");
int NumItems = 5; // how many cut widths to generate
int ClothWidth = 40; // width of the stock to cut the widths from
double efficiency = 0.7; // reject cut patterns less than this % used of the clothwidth
int maxPatterns = 100; // max # of patterns to generate
bool verbose = true; // set this to true if you want some (useful?) output
bool saveMpsFile = false; // set this to true if you want it to save an mps file in c:\\temp\\cutstock.mps
int itemSizeMin = 5; // minimum size for random generation of cut
int itemSizeMax = 10; // maximum size for random generation of cut
int itemDemandMin = 10; // minimum random demand for each cut
int itemDemandMax = 40; // maximum random demand for each cut
int seed = 12447; // use System.DateTime.Now.Millisecond; instead if you want a random problem.
if (verbose)
{
System.Console.WriteLine(String.Format("Random seed={0}\tmaxWidth={1}", seed, ClothWidth));
}
Random rand = new Random(seed);
int[] cuts = new int[NumItems];
int[] demand = new int[NumItems];
// item weights and demands
for (int cnt = 0; cnt < NumItems; cnt++)
{
cuts[cnt] = rand.Next(itemSizeMin, itemSizeMax);;
demand[cnt] = rand.Next(itemDemandMin, itemDemandMax);
if (verbose)
{
System.Console.WriteLine(String.Format("item[{0}]\tweight={1}\tdemand={2}", cnt, cuts[cnt], demand[cnt]));
}
}
List <int[]> patterns;
SolveKnapsack(maxPatterns, cuts, ClothWidth, efficiency, out patterns);
SimplexSolver solver2 = new SimplexSolver();
int vId = 0;
int[] usage = new int[patterns.Count];
// construct rows that make sure that the demand is met for each kind of cut
for (int cnt = 0; cnt < NumItems; cnt++)
{
solver2.AddRow(String.Format("item{0}", cnt), out vId);
solver2.SetBounds(vId, demand[cnt], Rational.PositiveInfinity);
}
int patCnt = 0;
if (verbose)
{
System.Console.WriteLine(String.Format("Generated {0} patterns", patterns.Count));
}
// set usage coeffs (A matrix entries) -- put the patterns as columns in the MIP.
Dictionary <int, int> patIdForCol = new Dictionary <int, int>();
foreach (int[] pattern in patterns)
{
int pId = 0;
String varName = String.Format("Pattern{0}", patCnt);
solver2.AddVariable(varName, out pId);
patIdForCol[pId] = patCnt;
solver2.SetIntegrality(pId, true);
solver2.SetBounds(pId, 0, Rational.PositiveInfinity);
for (int cnt = 0; cnt < NumItems; cnt++)
{
solver2.SetCoefficient(cnt, pId, pattern[cnt]); // set the coefficient in the matrix
// accumulate the quantity used for this pattern. It will be used to figure out the scrap later.
usage[patCnt] += pattern[cnt] * cuts[cnt];
}
patCnt++;
}
// set objective coeffs. --- the cost is the scrap
solver2.AddRow("Scrap", out vId);
for (int cnt = 0; cnt < patterns.Count; cnt++)
{
int colId = solver2.GetIndexFromKey(String.Format("Pattern{0}", cnt));
solver2.SetCoefficient(vId, colId, (ClothWidth - usage[cnt]));
}
solver2.AddGoal(vId, 0, true);
// invoke the IP solver.
SimplexSolverParams parms = new SimplexSolverParams();
parms.MixedIntegerGenerateCuts = true;
parms.MixedIntegerPresolve = true;
if (saveMpsFile)
{
MpsWriter writer = new MpsWriter(solver2);
using (TextWriter textWriter = new StreamWriter(File.OpenWrite("c:\\temp\\cutstock.mps")))
{
writer.WriteMps(textWriter, true);
}
}
solver2.Solve(parms);
if (solver2.LpResult == LinearResult.Optimal &&
solver2.MipResult == LinearResult.Optimal)
{
//Rational[] solutionVals = solver2.GetValues();
int goalIndex = 0;
// output if desired.
if (verbose)
{
System.Console.WriteLine("Solver complete, printing cut plan.");
foreach (int cnt in solver2.VariableIndices)
{
Rational val = solver2.GetValue(cnt);
if (val != 0)
{
if (solver2.IsGoal(cnt))
{
goalIndex = cnt;
System.Console.WriteLine(String.Format("Goal:{0}\t: {1}\t", val, solver2.GetKeyFromIndex(cnt)));
}
else if (solver2.IsRow(cnt))
{
System.Console.WriteLine(String.Format("{0}:\tValue= {1}\t", solver2.GetKeyFromIndex(cnt), val));
}
else
{
System.Console.Write(String.Format("{0}\tQuantity={1}:\t", solver2.GetKeyFromIndex(cnt), val));
for (int cnt2 = 0; cnt2 < NumItems; cnt2++)
{
System.Console.Write(String.Format("{0} ", patterns[patIdForCol[cnt]][cnt2]));
}
System.Console.WriteLine(String.Format("\tUsage:{0} / {2} efficiency={1}%", usage[cnt - NumItems], (int)(100 * (double)usage[cnt - NumItems] / (double)ClothWidth), ClothWidth));
}
}
}
System.Console.WriteLine(String.Format("Total scrap={0}", solver2.GetSolutionValue(goalIndex)));
}
}
else
{
System.Console.WriteLine("Generated problem is infeasible. It is likely that more generated columns are needed.");
}
Console.WriteLine();
}
public List <Bag.Item> LinearProgramming(List <Item> items)
{
List <Bag.Item> choosenItems = new List <Bag.Item>();
int itemsCount = items.Count;
double capacity = MaxWeightAllowed;
SimplexSolver solver = new SimplexSolver();
//double[] estimatedProfitOfProjectX = new double[] { 1, 1.8, 1.6, 0.8, 1.4 };
//double[] capitalRequiredForProjectX = new double[] { 6, 12, 10, 4, 8 };
//double availableCapital = 20;
//int[] chooseProjectX = new int[5];
double[] values = new double[itemsCount];
double[] weights = new double[itemsCount];
for (int i = 0; i < itemsCount; i++)
{
values[i] = items[i].Value;
weights[i] = items[i].Weight;
}
int[] chosenItems = new int[itemsCount];
//int profit;
//solver.AddRow("profit", out profit);
//solver.AddGoal(profit, 0, false);
int MaximumValue;
solver.AddRow("MaximumValue", out MaximumValue);
solver.AddGoal(MaximumValue, 0, false);
//int expenditure;
//solver.AddRow("expenditure", out expenditure);
//solver.SetBounds(expenditure, 0, availableCapital);
int MaximumWeight;
solver.AddRow("MaximumWeight", out MaximumWeight);
solver.SetBounds(MaximumWeight, 0, capacity);
//for (int i = 0; i < 5; i++)
//{
// solver.AddVariable(string.Format("project{0}", i),
// out chooseProjectX[i]);
// solver.SetBounds(chooseProjectX[i], 0, 1);
// solver.SetIntegrality(chooseProjectX[i], true);
// solver.SetCoefficient(profit, chooseProjectX[i],
// estimatedProfitOfProjectX[i]);
// solver.SetCoefficient(expenditure, chooseProjectX[i],
// capitalRequiredForProjectX[i]);
//}
for (int i = 0; i < itemsCount; i++)
{
solver.AddVariable(string.Format("Item{0}", i),
out chosenItems[i]);
solver.SetBounds(chosenItems[i], 0, 1);
solver.SetIntegrality(chosenItems[i], true);
solver.SetCoefficient(MaximumValue, chosenItems[i],
values[i]);
solver.SetCoefficient(MaximumWeight, chosenItems[i],
weights[i]);
}
//SimplexSolverParams param = new SimplexSolverParams();
//param.MixedIntegerGenerateCuts = true;
//solver.Solve(param);
SimplexSolverParams param = new SimplexSolverParams();
param.MixedIntegerGenerateCuts = true;
solver.Solve(param);
//Console.WriteLine(solver.MipResult);
//for (int i = 0; i < 5; i++)
//{
// Console.WriteLine("Project {0} is {1} selected.", i,
// solver.GetValue(chooseProjectX[i]) == 1 ? "" : "not ");
//}
//Console.WriteLine("The estimated total profit is: ${0} million.",
// (double)solver.GetValue(profit).ToDouble());
//Console.WriteLine("The total expenditure is: ${0} million.",
// solver.GetValue(expenditure).ToDouble());
//string result = "";
for (int i = 0; i < itemsCount; i++)
{
if (solver.GetValue(chosenItems[i]) == 1)
{
//result += "Selected Item " + i + " ";
choosenItems.Add(items[i]);
}
}
//result += " value "+(double)solver.GetValue(MaximumValue).ToDouble()+ " weight "+ solver.GetValue(MaximumWeight).ToDouble();
return(choosenItems);
}
protected static void CCN_Simplex()
{
int param1 = ReadSelectionInt("Max agents", 100, min: 1, max: 1000);
var param3 = ReadSelectionInt("Max time\"", 120, min: 10, max: 1200);
//Set agent shifts
var solveShifts = new CSP.ShiftsPlanner(param1);
TimeSpan ts8h = GetTimeSpanHours(8);
TimeSpan ts9h = GetTimeSpanHours(9);
TimeSpan ts10h = GetTimeSpanHours(10);
TimeSpan ts30mi = GetTimeSpanMinutes(30);
var shifts = new List <CSP.Models.Shift>();
shifts.Add(new CSP.Models.Shift(name: "A", start: GetTimeSpanHours(7), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "G", start: GetTimeSpanHours(8), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "B", start: GetTimeSpanHours(9), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "I", start: GetTimeSpanHours(10), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "E", start: GetTimeSpanHours(11), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "D", start: GetTimeSpanHours(13), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "C", start: GetTimeSpanHours(15), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "CL", start: GetTimeSpanHours(16), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "H", start: GetTimeSpanHours(17), duration: ts8h));
shifts.Add(new CSP.Models.Shift(name: "A++", start: GetTimeSpanHours(7), duration: ts10h));
shifts.Add(new CSP.Models.Shift(name: "B+", start: GetTimeSpanHours(9), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "B++", start: GetTimeSpanHours(9), duration: ts10h));
shifts.Add(new CSP.Models.Shift(name: "I+", start: GetTimeSpanHours(10), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "I++", start: GetTimeSpanHours(10), duration: ts10h));
shifts.Add(new CSP.Models.Shift(name: "E+", start: GetTimeSpanHours(11), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "E++", start: GetTimeSpanHours(11), duration: ts10h));
shifts.Add(new CSP.Models.Shift(name: "+D", start: GetTimeSpanHours(12), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "D++", start: GetTimeSpanHours(13), duration: ts10h));
shifts.Add(new CSP.Models.Shift(name: "C+", start: GetTimeSpanHours(15), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "CL+", start: GetTimeSpanHours(16), duration: ts9h));
shifts.Add(new CSP.Models.Shift(name: "++H", start: GetTimeSpanHours(15), duration: ts10h));
solveShifts.Shifts = shifts;
//Set requirements per shift
int[] liveData = new int[] { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 5, 6, 7, 9, 11, 22, 25, 21, 32, 44, 38, 33, 48, 41, 54, 50, 42, 43, 45, 60, 62, 56, 44, 33, 22, 11, 18, 16, 24, 28, 6, 12, 15, 8, 6 };
var requirements = new List <CSP.Models.HalfHourRequirement>();
TimeSpan ts = GetTimeSpanHours(0);
for (int i = 0; i < liveData.Length; i++)
{
requirements.Add(new CSP.Models.HalfHourRequirement(start: ts, requiredForce: liveData[i]));
ts = ts.Add(ts30mi);
}
solveShifts.HalfHourRequirements = requirements;
//pair shifts with vids
Dictionary <CSP.Models.Shift, int> shiftsX;
int vidGoal;
var SX = solveShifts.PrepareSimplexSolver(maxAgents: param1, shiftsExt: out shiftsX, vidGoal: out vidGoal);
var sxParams = new SimplexSolverParams();
ILinearSolution solution = null;
Task taskSolve = new Task(() =>
{
solution = SX.Solve(sxParams);
});
Stopwatch timer = new Stopwatch();
timer.Start();
taskSolve.Start();
TimeSpan limit = new TimeSpan(hours: 0, minutes: 0, seconds: param3);
while (!taskSolve.IsCompleted)
{
Console.SetCursorPosition(0, Console.CursorTop);
Console.Write(" {0:hh}:{0:mm}:{0:ss}", timer.Elapsed);
Thread.Sleep(millisecondsTimeout: 500);
}
Console.WriteLine("\n");
timer.Stop();
if (solution.Result == LinearResult.Feasible || solution.Result == LinearResult.Optimal)
{
Console.WriteLine(" solved as {1} after {0}", timer.Elapsed, solution.Result);
Console.WriteLine("Goal: {0}", solution.GetValue(vidGoal).ToDouble());
List <CSP.Models.ShiftForce> shiftsForce = new List <CSP.Models.ShiftForce>();
foreach (var shift in shiftsX)
{
var force = solution.GetValue(shift.Value).ToDouble();
shiftsForce.Add(new CSP.Models.ShiftForce(shift: shift.Key, force: (int)force));
}
solveShifts.ShowSolution(1, shiftsForce, showAgents: true, showSlots: true);
}
else
{
Console.WriteLine(" no solved :: {1} after {0}", timer.Elapsed, solution.Result);
}
}
