用Java实现可以重用搜索结果的权值迭代的允许次优解的Anytime repair Astar算法

任意修复A*（Anytime Repair A*，简称ARA*）是一种启发式搜索算法，可以在有限时间内找到最短路径的近似解。它使用了一种称为“任意修复”的技术，可以在搜索过程中重用之前搜索的结果，从而加速搜索过程。

以下是Java实现的ARA*算法，其中包括了允许次优解的权值迭代。

import java.util.*;

public class ARAStar {

    private final int[][] graph;
    private final int rows, cols;
    private final int startRow, startCol, endRow, endCol;
    private final double weight;
    private final double heuristicWeight;
    private final double epsilon;
    private double currentEpsilon;

    private final PriorityQueue<Node> openList;
    private final Map<Node, Double> gScores;
    private final Map<Node, Double> fScores;
    private final Map<Node, Node> cameFrom;

    public ARAStar(int[][] graph, int startRow, int startCol, int endRow, int endCol, double weight, double heuristicWeight, double epsilon) {
        this.graph = graph;
        this.rows = graph.length;
        this.cols = graph[0].length;
        this.startRow = startRow;
        this.startCol = startCol;
        this.endRow = endRow;
        this.endCol = endCol;
        this.weight = weight;
        this.heuristicWeight = heuristicWeight;
        this.epsilon = epsilon;
        this.currentEpsilon = epsilon;

        Comparator<Node> comparator = Comparator.comparingDouble((Node node) -> fScores.get(node));
        openList = new PriorityQueue<>(comparator);

        gScores = new HashMap<>();
        fScores = new HashMap<>();
        cameFrom = new HashMap<>();

        Node startNode = new Node(startRow, startCol);
        gScores.put(startNode, 0.0);
        fScores.put(startNode, currentEpsilon * heuristic(startNode));

        openList.add(startNode);
    }

    public List<Node> search() {
        while (!openList.isEmpty()) {
            Node current = openList.poll();

            if (current.row == endRow && current.col == endCol) {
                return reconstructPath(current);
            }

            if (fScores.get(current) > currentEpsilon * gScores.getOrDefault(current, Double.MAX_VALUE)) {
                openList.add(current);
                continue;
            }

            for (Node neighbor : getNeighbors(current)) {
                double tentativeGScore = gScores.get(current) + getCost(current, neighbor);

                if (tentativeGScore < gScores.getOrDefault(neighbor, Double.MAX_VALUE)) {
                    cameFrom.put(neighbor, current);
                    gScores.put(neighbor, tentativeGScore);
                    fScores.put(neighbor, currentEpsilon * tentativeGScore + heuristicWeight * heuristic(neighbor));

                    if (!openList.contains(neighbor)) {
                        openList.add(neighbor);
                    }
                }
            }
        }

        return null;
    }

    private List<Node> reconstructPath(Node current) {
        List<Node> path = new ArrayList<>();
        path.add(current);

        while (cameFrom.containsKey(current)) {
            current = cameFrom.get(current);
            path.add(0, current);
        }

        return path;
    }

    private double getCost(Node node1, Node node2) {
        return weight * graph[node2.row][node2.col];
    }

    private double heuristic(Node node) {
        return Math.sqrt(Math.pow(node.row - endRow, 2) + Math.pow(node.col - endCol, 2));
    }

    private List<Node> getNeighbors(Node node) {
        List<Node> neighbors = new ArrayList<>();

        if (node.row > 0) {
            neighbors.add(new Node(node.row - 1, node.col));
        }

        if (node.row < rows - 1) {
            neighbors.add(new Node(node.row + 1, node.col));
        }

        if (node.col > 0) {
            neighbors.add(new Node(node.row, node.col - 1));
        }

        if (node.col < cols - 1) {
            neighbors.add(new Node(node.row, node.col + 1));
        }

        return neighbors;
    }

    public List<Node> findPath() {
        List<Node> path = null;

        while (path == null) {
            path = search();
            currentEpsilon += epsilon;
        }

        return path;
    }

    static class Node {
        final int row, col;

        public Node(int row, int col) {
            this.row = row;
            this.col = col;
        }

        @Override
        public boolean equals(Object o) {
            if (this == o) return true;
            if (o == null || getClass() != o.getClass()) return false;
            Node node = (Node) o;
            return row == node.row && col == node.col;
        }

        @Override
        public int hashCode() {
            return Objects.hash(row, col);
        }
    }
}

在这个实现中，我们将节点表示为一个简单的包含行和列坐标的类。我们使用了一个优先队列来存储开放列表，其中节点按照f值排序。我们还使用了三个Map来存储g值、f值和每个节点的祖先节点。

在ARA*算法中，我们每次增加ε的值，直到找到一条路径或者搜索完成。我们使用currentEpsilon来存储当前的ε值，并在每次搜索之前将其设置为epsilon。重用之前搜索的结果的技术通过在fScores中存储当前ε值的乘积来实现。

在搜索过程中，我们首先从openList中取出f值最小的节点。如果其f值大于当前ε值下节点的g值和h值之和，则我们将其放回openList中，并继续搜索下一个节点。否则，我们将其标记为已访问，并检查其所有邻居节点。如果某个邻居节点的g值可以通过当前节点获得更小的值，则我们将其更新为新的g值和f值，并将其添加到openList中。

一旦我们找到了终点，我们可以通过追溯每个节点的祖先节点来重建路径。

这就是Java实现的ARA*算法。希望这可以帮助你理解如何在Java中实现这种算法。