问题描述
在我的项目中,我使用 or-tools 来解决 VRPTW 问题。 我需要为不同的节点设置不同的等待时间。 例如。我有 6 个地点。
- 车辆仓库。最大时间窗口 (0,1440)
- 客户 1 的上车点。时间窗口 (0,10)
- 客户 1 的交货点。时间窗口 (0,50)
- 客户 2 的上车点。时间窗口 (500,510)
- 客户 2 的交货点。时间窗口(500、600)
- 车辆维修点。最大时间窗口 (0,1440)
如果我用 addDimension
设置 slack_max
routing.addDimension(transitCallbackIndex,// transit callback
1440,// allow waiting time
60 * 24 * 2,false,// start cumul to zero
"Time");
我的车辆可以在每个位置的范围 (0,1440) 内等待时间。在这种情况下,时间超出了取货/交货节点的范围时间窗口。由于该节点的时间窗口是最大的,我如何只为 Vehicle 服务点设置 slack?
我试过这样设置松弛
if (index == 5) {
timeDimension.slackVar(index).setRange(0,1440);
}
但这并不像我预期的那样工作。
完整代码示例:
package test;
import com.google.ortools.Loader;
import com.google.ortools.constraintsolver.Assignment;
import com.google.ortools.constraintsolver.FirstSolutionStrategy;
import com.google.ortools.constraintsolver.Intvar;
import com.google.ortools.constraintsolver.IntervalVar;
import com.google.ortools.constraintsolver.RoutingDimension;
import com.google.ortools.constraintsolver.RoutingIndexManager;
import com.google.ortools.constraintsolver.RoutingModel;
import com.google.ortools.constraintsolver.RoutingSearchParameters;
import com.google.ortools.constraintsolver.solver;
import com.google.ortools.constraintsolver.main;
import java.util.Arrays;
import java.util.logging.Logger;
/** Minimal VRP with Resource Constraints.*/
public class Test {
// static {
// System.loadLibrary("jniortools");
// }
private static final Logger logger = Logger.getLogger(Test.class.getName());
static class DataModel {
public final long[][] timeMatrix = {
{0,0},{0,10,0}
};
public final long[][] timeWindows = {
{0,1440},10},// 1 from
{0,50},// 1 to
{500,510},// 2 from
{500,600},// 2 to
{0,// rest location
};
public final int[][] pickupDeliveries = {
{1,2},{3,4},};
public final int vehicleNumber = 1;
public final int depot = 0;
}
public static void main(String[] args) throws Exception {
Loader.loadNativeLibraries();
// Instantiate the data problem.
final DataModel data = new DataModel();
// Create Routing Index Manager
RoutingIndexManager manager =
new RoutingIndexManager(data.timeMatrix.length,data.vehicleNumber,data.depot);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
Solver solver = routing.solver();
// Create and register a transit callback.
final int transitCallbackIndex =
routing.registerTransitCallback((long fromIndex,long toIndex) -> {
// Convert from routing variable Index to user NodeIndex.
int fromNode = manager.indexToNode(fromIndex);
int toNode = manager.indexToNode(toIndex);
return data.timeMatrix[fromNode][toNode];
});
// Define cost of each arc.
routing.setArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Add Time constraint.
routing.addDimension(transitCallbackIndex,// start cumul to zero
"Time");
RoutingDimension timeDimension = routing.getMutableDimension("Time");
// Add time window constraints for each location except depot.
for (int i = 1; i < data.timeWindows.length; ++i) {
long index = manager.nodetoIndex(i);
if (index >= 0) {
timeDimension.cumulVar(index).setRange(data.timeWindows[i][0],data.timeWindows[i][1]);
}
if (index == 5) {
timeDimension.slackVar(index).setRange(0,1440);
}
}
// Add time window constraints for each vehicle start node.
for (int i = 0; i < data.vehicleNumber; ++i) {
long index = routing.start(i);
timeDimension.cumulVar(index).setRange(data.timeWindows[0][0],data.timeWindows[0][1]);
}
// Instantiate route start and end times to produce feasible times.
for (int i = 0; i < data.vehicleNumber; ++i) {
routing.addVariableMinimizedByFinalizer(timeDimension.cumulVar(routing.start(i)));
routing.addVariableMinimizedByFinalizer(timeDimension.cumulVar(routing.end(i)));
}
// Define Transportation Requests.
for (int[] request : data.pickupDeliveries) {
long pickupIndex = manager.nodetoIndex(request[0]);
long deliveryIndex = manager.nodetoIndex(request[1]);
routing.addPickupAndDelivery(pickupIndex,deliveryIndex);
solver.addConstraint(
solver.makeEquality(routing.vehicleVar(pickupIndex),routing.vehicleVar(deliveryIndex)));
solver.addConstraint(solver.makeLessOrEqual(
timeDimension.cumulVar(pickupIndex),timeDimension.cumulVar(deliveryIndex)));
}
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
main.defaultRoutingSearchParameters()
.toBuilder()
.setFirstSolutionStrategy(FirstSolutionStrategy.Value.PATH_CHEApest_ARC)
.build();
// Solve the problem.
Assignment solution = routing.solveWithParameters(searchParameters);
if (solution == null) {
System.err.println("No solution found");
return;
}
// Print solution on console.
printSolution(data,routing,manager,solution);
}
/// @brief Print the solution.
static void printSolution(
DataModel data,RoutingModel routing,RoutingIndexManager manager,Assignment solution) {
RoutingDimension timeDimension = routing.getMutableDimension("Time");
long totalTime = 0;
for (int i = 0; i < data.vehicleNumber; ++i) {
long index = routing.start(i);
logger.info("Route for Vehicle " + i + ":");
String route = "";
while (!routing.isEnd(index)) {
Intvar timeVar = timeDimension.cumulVar(index);
route += manager.indexToNode(index) + " Time(" + solution.min(timeVar) + ","
+ solution.max(timeVar) + ") -> ";
index = solution.value(routing.nextvar(index));
}
Intvar timeVar = timeDimension.cumulVar(index);
route += manager.indexToNode(index) + " Time(" + solution.min(timeVar) + ","
+ solution.max(timeVar) + ")";
logger.info(route);
logger.info("Time of the route: " + solution.min(timeVar) + "min");
totalTime += solution.min(timeVar);
}
logger.info("Total time of all routes: " + totalTime + "min");
}
}
解决方法
在您的代码中:
// Add time window constraints for each location except depot.
for (int i = 1; i < data.timeWindows.length; ++i) {
long index = manager.nodeToIndex(i);
if (index >= 0) {
timeDimension.cumulVar(index).setRange(data.timeWindows[i][0],data.timeWindows[i][1]);
}
if (index == 5) {
timeDimension.slackVar(index).setRange(0,1440);
}
}
我认为:
- 此处您的
if
条件应使用i
, - 由于您的循环从
1
开始,您已经跳过了仓库(节点0
), - 您的
timeWindows
结构已经包含节点 5 的[0,1440]
。 - 要将 P&D 节点的 slack 强制为零,您应该使用
SetValue()
所以你可以像这样重写它:
// Add time window constraints for each location except depot.
for (int i = 1; i < data.timeWindows.length; ++i) {
long index = manager.nodeToIndex(i);
timeDimension.cumulVar(index).setRange(data.timeWindows[i][0],data.timeWindows[i][1]);
if (i == 5) {
timeDimension.slackVar(index).setRange(data.timeWindows[i][0],data.timeWindows[i][1]);
} else { // disable waiting time for Pickup&Drop location
timeDimension.slackVar(index).setValue(0);
}
}
可能的输出:
$ mvn exec:java
[INFO] --- exec-maven-plugin:3.0.0:java (default-cli) @ test ---
Dec 22,2020 12:40:45 PM Test printSolution
INFO: Route for Vehicle 0:
Dec 22,2020 12:40:45 PM Test printSolution
INFO: 0 Time(0,0) -> 1 Time(0,10) -> 2 Time(10,20) -> 5 Time(10,20) -> 3 Time(500,500) -> 4 Time(510,510) -> 0 Time(510,510)
Dec 22,2020 12:40:45 PM Test printSolution
INFO: Time of the route: 510min
Dec 22,2020 12:40:45 PM Test printSolution
INFO: Total time of all routes: 510min
最后一个问题,您所说的“但没有按我的预期工作”是什么意思。 观察到的输出是什么?您期望什么?