幅優先探索で迷路の特定のスタート地点からゴール地点までの最短距離を出力するプログラム

## ■**概要**

迷路の最短距離を幅優先探索（BFS）で求めるプログラムを実装しました。

基本的なアルゴリズムに対する理解を深め、実際に活用できるようになりたいと思い、今回は幅優先探索の問題を解きました。

以下、解説をしていきます。

※読んでいるだけで理解が難しい場合は、実際にpaiza.IOなどの実行環境に貼り付けて、適宜console.logを入れて処理を追っていただけると内容が理解しやすくなると思います。

[https://paiza.io/ja](https://paiza.io/ja)

## **■問題**

**AtCoder Beginner Contest 007 atcoder C \- 幅優先探索**

[https://atcoder.jp/contests/abc007/tasks/abc007\_3](https://atcoder.jp/contests/abc007/tasks/abc007_3)

AtCoderは競技プログラミングの問題を出題するサイトで、定期的にコンテストを開催しています。

今回解いたのはAtCoder Beginner Contestと呼ばれる、初心者向けの問題になります。

入力例

```
7 8  
2 2  
4 5  
########  
#......#  
#.######  
#..#...#  
#..##..#  
##.....#  
########
```

まず、問題の要件を洗い出します。

・スタート地点：(2,2)  
・ゴール地点：(4,5)  
・通行可能：.  
・通行不可：\#  
・スタートからゴールまでの最短マス数を求める

問題文が長いため、

・特に重要そうな条件を書き出す  
・タイトルに「幅優先探索」とある→幅優先探索を使いどのように解くか方針を決める

に重点を置いて進めていきます。

## **■幅優先探索とは？**

グラフ探索アルゴリズムの一つで、ノードの隣接するノードを全て探索、さらに隣接するノードを全て探索……と繰り返していき、隣接するノードがなくなるまで探索を繰り返していくアルゴリズムです。

![Untitled.png](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/3876928/4728fdcb-0924-c56f-2f04-1342a603a1b6.png)


引用元：atcoder

[https://atcoder.jp/contests/abc007/tasks/abc007\_3](https://atcoder.jp/contests/abc007/tasks/abc007_3)

注意点として、訪問済みのノードに対しては再度探索は行わないようにする処理が必要になります。

この処理がないと例えば、

スタート地点→右隣のマス→その左隣のマス（つまりスタート地点）→その右隣のマス……

というように、探索が無限に繰り返されてしまいます。

類似したアルゴリズムに「深さ優先探索」があります。

## **■幅優先探索と深さ優先探索の違い**

|  | 概要 | 探索するマスを管理する配列 | 配列の管理方法 | メリット | デメリット |
| ----- | ----- | ----- | ----- | ----- | ----- |
| 幅優先探索 | 隣接するノードをすべて探索してから、さらに隣接するノードを探索する。別名BFS | キュー | FIFO | 全方向に対して探索を繰り返すので、ゴール地点に短時間で到達できる可能性がある | キューのメモリ量が多くなる可能性がある |
| 深さ優先探索 | 隣接するノードに対し、一方向に進めるだけ進み、行き止まりになったら一つ前のノードに戻って別の方向に探索する。別名DFS | スタック | FILO | 一方向に対して探索するので、スタックのメモリ量が少なくて済む可能性がある | ゴール地点に到達するのに時間を要する可能性がある |

※メリット、デメリットを可能性がある、としているのは、データの構造により必ずしも当てはまるとは断言できないためです。

例として以下の二分木で幅優先探索と深さ優先探索の違いを確認してみます。

スタート地点はaとします。

番号は探索する順番になります。

### **・幅優先探索**

![Untitled (1).png](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/3876928/24c49c07-18fd-8b7c-5626-d2967b4093c3.png)


aに隣接するb,c→bに隣接するd,e→c(隣接無し)→d(隣接無し)→eに隣接するf→f(隣接無し)

と探索しています。

### **・深さ優先探索**

![Untitled (2).png](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/3876928/747b1a6b-3d25-c3c4-3775-822c831f1116.png)

aに隣接するb,c→c(隣接無し)→bに隣接するd,e→eに隣接するf→f(隣接無し)→d(隣接無し)

と探索しています。

## **■問題を解くにあたり、特に重要そうな条件を書き出します**

* 入力の情報
  * y方向の行数、x方向の行数、(yの開始地点,xの開始地点)、(yのゴール地点,xのゴール地点)  
    * yとxの順が逆なので注意  
    * 全て1で始まる(0開始ではないので注意)

* 地図
  * #は通行不可  
  * .は通行可能  
  * スタートとゴールは必ず通行可能  
  * スタートからゴールへは必ず到達可能  
  * 隣接するマス同士の距離は必ず1

* 幅優先探索で、スタートからゴールまで最小移動マス数で移動するよう計算する
  1. スタート地点から、隣接する移動可能なマスを調べ、距離を設定する  
  1. 他に隣接するマスに対しても1を行う  
  1. さらに隣接するマスに対しても、1,2を行う  
  1. ゴール地点に到達するまで繰り返す  
       * 探索するマスは作業用キューで管理する  
         * 作業用キューの先頭に追加する(shift)  
         * 作業用キューの末尾から取り出す(pop)

## **■コード**

```
process.stdin.resume();  
process.stdin.setEncoding("utf8");

var lines = [];  
var reader = require("readline").createInterface({  
  input: process.stdin,  
  output: process.stdout,  
});

reader.on("line", (line) => {  
  lines.push(line);  
});

reader.on("close", () => {  
  const [maxY, maxX] = lines.shift().split(" ").map(Number);  
  let [startY, startX] = lines.shift().split(" ").map(Number);  
  let [goalY, goalX] = lines.shift().split(" ").map(Number);  
    
  // 入力値は全て1で始まるが、この先配列の添字に使う関係で全て-1する  
  [startY, startX, goalY, goalX] = [  
    startY - 1,  
    startX - 1,  
    goalY - 1,  
    goalX - 1,  
  ];

  // 地図、距離を保管する配列(初期値は-1)を生成する  
  let map = [];  
  let distance = [];  
  for (let i = 1; i <= maxY; i++) {  
    map.push(lines.shift());  
    distance.push(Array(maxX).fill(-1));  
  }

  function bfs(startY, startX, goalY, goalX, map, distance) {  
    distance[startY][startX] = 0;

    // 作業用キューの初期化  
    let queue = [];  
    queue.push([startY, startX]);

    // キューが空になるまでループ  
    while (queue.length != 0) {  
      // キューの先頭から座標を取り出す（幅優先探索の場合）  
    　// 深さ優先探索にしたい場合はshift->popにする  
      let [y, x] = queue.shift();

      // 四方向（上下左右）のマスをチェックする  
      let nextPos = [  
        [0, 1], // 右  
        [1, 0], // 下  
        [-1, 0], // 上  
        [0, -1], // 左  
      ];  
      // 各方向に対して通行可能かつ未訪問であれば処理を行う  
      nextPos.forEach((value) => {  
        let [addy, addx] = [value[0], value[1]];

        // 通行可能で、距離が-1（未訪問）であれば更新し、キューに追加  
        if (  
          map[y + addy][x + addx] == "." &&  
          distance[y + addy][x + addx] == -1  
        ) {  
          // 新しい距離を設定  
          distance[y + addy][x + addx] = distance[y][x] + 1;  
          // 隣接するマスを次に探索するためにキューに追加  
          queue.push([y + addy, x + addx]);  
        }  
      });

      // 追跡用のコメント  
      // console.log("distance", distance);  
      // console.log("queue", queue);  
      // console.log("--------------");  
    }  
      
    // ゴール地点までの距離を返す  
    return distance[goalY][goalX];  
  }

  console.log(bfs(startY, startX, goalY, goalX, map, distance));  
});
```

## **■コードの説明**

### **変数・配列の概要**

・startY, startX, goalY, goalX：入力値は全て1で始まりますが、この先配列の添字に使う関係で全て-1します。  
・map配列：迷路の地図を格納する配列です。  
・distance配列：地図のマスに対応する場所の、スタート地点からの距離を格納します。初期値は-1。-1であれば未訪問、つまり探索の対象と判断できます。  
・queue配列：作業用キュー。探索の対象となるマスの座標を入れます。pushで追加し、shiftで取り出します（FIFO）。

### **bfs関数のwhileループ内の処理**

・上下左右全方向のマスをチェックします。  
・通行可能で、距離が-1(=未訪問)であれば、距離を設定します。  
・作業用キューに追加し、隣接するマスのさらに隣接するマスを探索します。  
・作業用キューが空になるまで繰り返します。

## **■実際に動かして追跡してみる**

### **map配列**

・迷路のレイアウトを示しています。  
・Sがスタート地点、Gがゴール地点を表しています。  
わかりやすくするためにこの表記をしており、実際は.が入っています。  
・\#は壁を、.は通行可能な道を示します。

```
[  
  [ # , # , # , # , # , # , # , # ],  
  [ # , S , . , . , . , . , . , # ],  
  [ # , . , # , # , # , # , # , # ],  
  [ # , . , . , # , G , . , . , # ],  
  [ # , . , . , # , # , . , . , # ],  
  [ # , # , . , . , . , . , . , # ],  
]
```

### **distance配列・queue配列**

・初期値

```
[  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1]  
]
```

スタート地点から隣接するマスの更新が終わった時の状態
※queueに入っているマスの隣接するマスの座標の距離を次に計算します。
```
distance [  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1,  0,  1, -1, -1, -1, -1, -1],  
  [ -1,  1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1]  
]  
queue [ [ 1, 2 ], [ 2, 1 ] ]
```

[ 1, 2 ]に隣接するマスの更新が終わった時
```
distance [  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1,  0,  1,  2, -1, -1, -1, -1],  
  [ -1,  1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1]  
]  
queue [ [ 2, 1 ], [ 1, 3 ] ]
```

[ 2, 1 ]に隣接するマスの更新が終わった時
```
distance [  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1,  0,  1,  2, -1, -1, -1, -1],  
  [ -1,  1, -1, -1, -1, -1, -1, -1],  
  [ -1,  2, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1]  
]  
queue [ [ 1, 3 ], [ 3, 1 ] ]
```

(以下ゴールに到達するまで繰り返し)

最終的なdistanceの中身
```
distance [  
  [ -1, -1, -1, -1, -1, -1, -1, -1],  
  [ -1,  0,  1,  2,  3,  4,  5, -1],  
  [ -1,  1, -1, -1, -1, -1, -1, -1],  
  [ -1,  2,  3, -1, 11, 10, 11, -1],  
  [ -1,  3,  4, -1, -1,  9, 10, -1],  
  [ -1, -1,  5,  6,  7,  8,  9, -1],  
  [ -1, -1, -1, -1, -1, -1, -1, -1]  
]  
queue []
```

ゴール地点の座標でdistance配列にアクセスした値をreturnするので、最終的なスタート地点からゴール地点までの最短経路距離が返ってきます。

## **■深さ優先探索で求めたい場合**

作業用キューから取り出す以下の処理のshiftをpopに変更します。
```
let [y, x] = queue.shift();   
-> let [y, x] = queue.pop(); 
```
console.logで仕込んだqueue(作業用キュー)の中身が、shiftとpopでどう変わるかを見てみましょう。

### **■幅優先探索(shift)の場合**

隣接する上下左右のマスを全て調べる→さらに隣接する上下左右のマスを全て調べる、という方法で探索しています。
```
queue [ [ 1, 2 ], [ 2, 1 ] ]  
queue [ [ 2, 1 ], [ 1, 3 ] ]  
queue [ [ 1, 3 ], [ 3, 1 ] ]  
queue [ [ 3, 1 ], [ 1, 4 ] ]  
queue [ [ 1, 4 ], [ 3, 2 ], [ 4, 1 ] ]  
queue [ [ 3, 2 ], [ 4, 1 ], [ 1, 5 ] ]  
queue [ [ 4, 1 ], [ 1, 5 ], [ 4, 2 ] ]  
queue [ [ 1, 5 ], [ 4, 2 ] ]  
queue [ [ 4, 2 ], [ 1, 6 ] ]  
queue [ [ 1, 6 ], [ 5, 2 ] ]  
queue [ [ 5, 2 ] ]  
queue [ [ 5, 3 ] ]  
queue [ [ 5, 4 ] ]  
queue [ [ 5, 5 ] ]  
queue [ [ 5, 6 ], [ 4, 5 ] ]  
queue [ [ 4, 5 ], [ 4, 6 ] ]  
queue [ [ 4, 6 ], [ 3, 5 ] ]  
queue [ [ 3, 5 ], [ 3, 6 ] ]  
queue [ [ 3, 6 ], [ 3, 4 ] ]  
queue [ [ 3, 4 ] ]  
queue []
```

### **■深さ優先探索(pop)の場合**

一方向に対し隣接するマスを調べる→さらにそのマスに隣接するマスを調べる→隣接するマスがなくなるまで続け、なくなったら一つ前に戻って別の方向に探索する、という方法で探索しています。
```
queue [ [ 1, 2 ], [ 2, 1 ] ]
queue [ [ 1, 2 ], [ 3, 1 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 4, 1 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 4, 2 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 2 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 3 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 4 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 5 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ], [ 4, 5 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ], [ 4, 6 ], [ 3, 5 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ], [ 4, 6 ], [ 3, 6 ], [ 3, 4 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ], [ 4, 6 ], [ 3, 6 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ], [ 4, 6 ] ]
queue [ [ 1, 2 ], [ 3, 2 ], [ 5, 6 ] ]
queue [ [ 1, 2 ], [ 3, 2 ] ]
queue [ [ 1, 2 ] ]
queue [ [ 1, 3 ] ]
queue [ [ 1, 4 ] ]
queue [ [ 1, 5 ] ]
queue [ [ 1, 6 ] ]
queue []
```

[image1]: 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>

[image2]: 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>

[image3]: 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dNnfvyKayPz268pmj1rCrScc9F1rx3QGWKT7GJpyusVSPEpLiZb3uZjpX45ytbB1S7K6UTwAeOjKquLaR7XgZeW5J3+pTvu2jf4/qQm7/TuLll5Fuzzqor/0Lgmh9inJgP8CLB7g8zHLcDLTlnHAH9CKpejUEZ6dFfT0VP7w307O/55TLgp90rbA7DDuad9fP/x2RVSRB0dHfgRqKrK27wRDvOvqKjgDX5VKpejGIE494nMxwzoStt/jbfZ0oGOR2Bv2QtXvZmIuYa8E/aVaWho4A2eqa+vDz50uACx1AEggUrZcrS6uhojsLu7m7e5JN07cnY1sr3uZtjV5V++k7f4XuxTEwHXAli2bJntJ/L2AAdSlZeXiyYfQmqWo1ACZWZmwm+hu1WoKFaXOpjgaGTg0IHWRzbnzpm68MxLOt98h7cns4qLi+HkBINB3uCxIObxC6DGqwZ2ohQsR9mSerW1tTIfSxBbO3bsiJSR2dk2ip8t3y4vKPjYmUsWzFnwga/ccefufe/wHsksOCFwWuDk8Ia4CDuX1tfX8wb/KQXLUUhKSvSWCW/wTNg1GQpg3mCkaBAW5K88J2t6xuIV59c9+OsjfuhGZVHsU+OgsbFRiU76JJriAFANZWRkFBUViSa/QaqVo0NjE9HDZ8DbPJOqqlD5QP1jb2330PB7e1545tOXnDVpytSvfb8h+aJQIsxFzjo2OBI+SeJb/adUK0eh/FDGJqKX+VgFMyovL1eiC6HxBtMafH3HLEXJXHDmi/uO8Lbk1Lx58+CHCXtHJET4obS0tPAGn+n47wT+oQVkrdVQuvuxCuJbWwIIPyhCWBrU9WHw+MP/Cb/WzU91iSYODAXXP5AM4WvnYGTA8EUfUJTJs37x51d4i78lni4EJTotha4pPlBVVYW3hUSTryAxF82xpXugZgCqQSXat1M06cKWW68B/00NbaKJg3BUsWH16tWwt6amJtFkDkYuOR12MPNnT/xTMPkadIXP6IuLi3lDLI32v/na3XfecflFF2KX2uuu+/zm/3mk7+Ag72hO8Fko0af2vMFnkmbCRMGoA8FvHpx0+P3jDRKxIOQN48WOKjZw767rEwOG9/9tbroyJeuUna8ekvkkEdg4Gy/ufPSsRZG7qUvPLbihrKykZM3Js6fCn1d8+T9EZzOgqipsXlBQIJp8BdIg5FzNSHc/VkF8a/OATyZaW1tFky5wQajrg2BG3d3diqYAk6ml4QdVm3/17tFj2sZjRw/f+aWrYPMLrv7aEa0hGSSerrD1IOx79S9nnTJDmX7i/b9+KjRy3BQaeufhH33r0xvukW0VG9RkCcKw/6R7oGYAg1CNPp+V+WhhXDk6Ejp44E3Ydu++A6FjI5xz5LBMAAahronB9i23Tpo8dVnBZXff+8DzL74I7/jE47/+fMnF6WmTTl36sWfVA7pb+Rl0xYKQN0j0w3+D36BJX7xTp3fb4OB7fJM5qZog9LOkmTBRMGpXeGskEAiY70HGgvCVXW2fu+6KUxfMgj+nz5lf9KkbX9v3/myz7KgMQXtbSOaz9+87b1xzxfT0dEWjyVOmrv7MV7t6IhGou1XSgcVM2J8/N33KzHlPvPy2YLIParJkQvYH/s2AczUj3f1YBfGtTYI6dsZFkwwwCD968cWzpilZ8xeuuhCUP2d2JjTOOfPC7n0DzNmk8MlYW1sbbxA1PPzss+2//OWD8GXdvv3xgwcHeYfkke65tRSEoTfapynKyXmFfa7O/KkmSxCG/SfdAzUEVROEMh8OMAhnzFrwg3v+u2f/wWMjoNDel5+9JjIfs3J1Rd3ImDM7sNjAglA0pTDoit2p5g16OvTCbxVck4y3OBJOKuX/9RKlmTBRMGpX6vggNCMMwtvu5Vdm7ev6AxSmsxedqx6K/DKzozIEbSaU+UwcUEw/J3zvn63gPH9FMS7FoutjA5LmOSH7A/9mwLmake5+rIL41iZBtVuO6t4dXXPuiUrGSc279mKLSVkoR1NIuucWXletWoU9ZkQTD8N78tKVmfOWvnwwctNY38c6FBYWwsfR3d0tmnwFqVOO9vf350ZlfomCGA/r//2alYqSsWX7c9gSOSwTEAgEcPiMaEphkAlntWhubuYNOhq57oJTlCkz7v3tLt5iV0NDQzk5OfArwBv8J2kmTBSMOpD2EYUZxXhYv6nsUkWZXPuLP49qjsoQzBdgEwGgIlDG5iyX+TB4svEHUycrp37o0p7+yMwCzDS477Wf/CzS+VN3qxiA756oMRyWQBqEnKsZ6e7HKohvbR60MynIfLQQoxy98bIzFGXGA394HlvMCAcW5ufn84ZUl+65RcBxDKbmXAoNbvrXK9MU5dSlH/rB5gda29qam5sq139h/szpBTd9j3c2AUVFRezSQObjE0idcnR0rNtaZWWlaNIFWTk6Mtz34bmTp8zK2flqP7ZEDssINm/erGgeT+v6pCTEEN4aMdl7M3T4nQfv+fbyJQtmzIjM0j1pSvpJcxd8/KprHt1puUbFnqvLli1zcZ5v7yTNhImCUQeCX1xtQWgoWTnasvXr0H7mxZ8djPYtY0cVG7AYbm9vF00TFrRzLsl8ODh6dLCzcxdksCeffqanz+bMNFgTmXxKmXCQBiHnaka6+7EK4ltbApxmm03zrOvDAIPw4qu//Kfn/vbOYORSZLBv78/vvmPOzPS0adkPP/kyczaUOKPRxJHuuWUQ/zmX8LOwFPmJhZQqR0Gtra1paWmBQEA0iYBBOHPmrLSMaacsWAgpdMHckyZPUqZMPeGOHz+KE02gMzswGeCMRji/sMwnVSG2cM4l+FCwY73XYlMr4OPBpJA0EyYKRh0Lnw61tLTwBkHRQb03/e6JXffc+a3zli9NT1fS00+8dPWnHvn9Lq0bOyoZ4HQmisk7EBMPcLIZqEtFk+uA8/3k5eWJJt+CNAg5VzPS3Y9VEN/aKsAvrhJddAkvynV9rEJs4Y24+vp63jAxJJ4uEXAiZjNLJjkBXPgJZ76T+fgQUq0cBQiFQpgM8bpc18cqhKPSBbwly27E6fqkNphRf3+/duEA3uyGIN+yhZ94m78lzYSJglE3pF2dh7dZFzsqEXbs2IHrPdFNUUPQLhwg87ENbPlRXI9J18e3IA1CztWMdPdjFcS3tgfaT0XmYx501dbWlpkZGffk1npPSSrxdMmALRywatUqNjm6zNkkQF7F60D2myv6+BxSsBxloK1PZD4mIRyVFiAHYgRWV1fLfCYIWFJPTw+ufJyTk9PQ0DAwEBm0aVtQgOD8WnAdmHRVKJM0EyYKRl1VTU2N9jfSnthRMWBVKPyim+8vTsAA+3Yr0VEvJuen5ACiF59AKtF7oUl9X1oahJyrGenuxyqIb+0QWF0KlyKqqur6GAITfNjsCzTBq1Am8XSZAYg97GOkRCdrrq+vV8d63ovODKD4hKuAsrIyLEPgpzA4ttqM6JwskMrlKIPm5ma8FGElkOgTG8LRp8BNTU3a/TDTBAfbgg8CTiOcUvyVhIjKzc2tqqqqra1VxwvOPLQXFhbCmce4BSgvL8cEmOySZsJEwag30mawZcuWQRJjfZoMBd8V+LkNBAK4OWZUNLEDJnACkBVZcjMUpk1PnzfGGaRByLmake5+rIL41i4CfNjYtRcFV3R1dXVQ3ojzo3V1dUE7fNj4IJ4JV/khaSU72zagu7sbfu/gJ7JgvCoqKqAdV5UQt0p2mBDlKAP4uYWSpr29vbKyEoe6oaAcwlH5TNpfZax8Wltbtes9sUMlIDmUNBMmCkY9E/bwxF6FKMh1kAkhMrl0p0STJLRXV1eDD6t82MqH7DgJCJyDNAg5VzPS3Y9VEN/aLcDuGqyHp66PDFBwcYjJUDU9g8ZEkHi6CCzBRClHsYfn6tWr7fXqDkcFABcnyoQcPh8DSA4lzYSJglEPxDIY6+FpSeyowtEOkEoS9tMn8DNIg5BzNSPd/VgF8a2dA67YiqvYy3xig1a2V6hPVYmni8ASpH45qgoLyos+hhA5rDFgOxRNExNIDiXNhImCUbflPHGxo2LABu+LJgICqyANQs7VjHT3YxXEt3YCOBcou4TT9TEDnLSD93nbxJN4uggsQSqXo2yIfUNDg8zHJISjYsD27GCF+tQBkkNJM2GiYNQ9uZWv2FFpgZtvW9eHgMAMSIOQczUj3f1YBfGt7UF/f/+8efPwyk3mYx50Bftnqw5NZImni8ASpGw5WldXp0TXAxFNNiAcFQfcW+j6TAQgOZQ0EyYKRt1Qd3e3i2mKHRUHLNn6fwU8Aj+DNAg5VzPS3Y9VEN/aBqxbt06JrgwjmuyBTFu3boU3grfjDRNJ4ukisAQpWI5C9sOhSS7O/hKOSoSenh72XjKflAeSQ0kzYaJg1LFKS0shO9XU1PAGu2JHpQuYdSEliiYCAjMgDULO1Yx092MVxLe2BNplD2Q+NiCG4IIQ3xET7wSUeLoILEGqlaOBQIAtACTzsQHhqGRQVlYGcVhXVyeaJgKQHEqaCRMFow6Ea+UWFhbyBmdiRyUDXB49PqsOEaQeSIOQczUj3f1YBfGtTQJbFHbHjh0yH9tgKJxVGt6aN0wAiaeLwBKkTjnKlkcXTc4hHFUMaGpqwiQcCoVkPqkKJIeSZsJEwagt9fb2ZmdnK9FlOnmbY7GjigFDQ0M4MSlcjsp8CAh0QRqEnKsZ6e7HKohvbQZwurQNGzaIJlfAjHAaG9evSP0v8XQRWIJUKEc7OjqU8ct0ij4OIRxVbMDF2eGiVFVVmU9KAsmhpJkwUTBqUfDVx3VFcNCgF2JHZQjV1dUsIct8CAg4kAYh52pGuvuxCuJbxwackBfiEFe60/VxDibl6aWpbyWeLgJLkNzlKNSf2qnpdX1cgchhmYPKykp2k1bmk2JAcihpJkwUjFoRTuLk9SIt7KjMQHt7O16gOpncjWBCgTQIOVcz0t2PVRDfWgbcPLy6Pm6BJeHCT95do/pN4ukisARJXI6yGelFk+sQjsokiHdrRZ9UApJDSTNhomDUnHDV+Hnz5vX19fE2t8WOyjzgc0tcfEbmQ0CAIA1CztWMdPdjFcS31gWccRBXjZf5uAhWhV26vb5Y9YnE00VgCZKyHG1tbU1LSwsEAqLJIwhHZR6427a6PikDJIeSZsJEwagJ4fRKjY2NvMEbsaOyBLSiKIFJkAYh52pGuvuxCuJbc1BTUwNf7tLSUtHkHdiQw/XYkkji6SKwBElWjvb09OTm5mZkZOBchro+XkA4KquAg4xx0jeZTwoAyaGkmTBRMBpTOIlTnKcYZEdlFWhFUQIzIA1CztWMdPdjFcS3ZgDZLzMz0/VJnMyAbTlfmM3/Ek8XgSVIpnKUm09J18cjCEdlA9TxS5Tq+iQ7kBxKmgkTBaMStbS0KAmaWZAdlT3AxbqDwaBoIiAYTZZyVDt5hMzHU3Ait1Zos6Guvz3d1vbE3r53eYOrEk8XgSVIjnIUn7nhNEri/xAHCEdlDxK1ouhLf3p4zrQpipKxZftzMh9XgORQ0kyYKBgVxEbKJmpCQXZUtiH+K4ruf+Wv5yyaqUQUCUJdHwKfgDQIOVcz0t2PVRDfWjtnhMzHa3CuVatWKfHq5XO479WiwOKZc5YXnLuYBaF3Ek8XgSXwezna0dHBzZ4k/g/6MHJsb/fft3zv9quKPn7Waafl5uZ+6MJPvrAvcnWk42wE0eNyBLiiaElJiWhyF0JDB8s/ce60rJN/9sd/3HrNeVSO+l/STJgoGB0vHCBbW1vLtRtp+P47/u2U2ZmKMu28j1352c+WlX3mM+cvW/WUamfcEzsqJxCnFUVDQzVfvVpJn/mdYGSRcBaE+s4E/gBpEHKuZqS7H6ugfWvtVBGcKQaMhIbqKj8JG64q+dzzrx+POpmzSXBF3q8oeuyXtTenK8pXa34RuX81Pgi9k3i6CCyBf8vRoaGh1atXK9EnbLqHLoO/bP/xCVMmrSj63P53I48EdH2sQvS4nAIkQ9bxVebjBNq3b80+If2Sf71tKHS8hcrRpJA0E8YHent7g1EVaFRRUQEt2OErLy8veoCmdeTgJ1Z+QFFm/emVd3iTXeHRugK4oihOySHzsQf7XnziAydOP+P86/a+e4SZqBxNCpAGIedqRrr70QXICXV1dXjDMLaKiorYuFjxqER4+Ymfz5yifHDNzaLJCbglj1YU3a8+e8GSOXOXrny+55C2ncrRpIB4l6Pw5YNLI7xFAYLyrLKyEjKDqlFTUxO0FBYWZmVlgQ/Ub8XFxXB9GJb8D1p4+K4vwyZf+eEvD729/7knHrvnh9+DXf3oJw90/OPV4dCIbCtDwIN3BbxYUbT+tlJl2pyf/v8/qeN1U1FAUaZ+t/43wD29fbLNHQLJoaSZ0AvYsWPH8uXLMfzgu9jW1ib6RA/nuFRVra+vh4oUN9m4cSObzFOmb1x7gaJMvuiyK5YsOhm3Oq706Zdf+6XdBw7zG5gQOypXQDsWhDNhZY7atm2b7ua6sOVr1477Z/WUe/mNss0JEgvSIORczUh3PwhDQ0MQTvhtKCkpgapM9OHeUQvwpcSsCBUsDucVfRBuuPg0cFu84iPfu6+ha89boUivsYG/PLn9k+efA+1nXLD2rcNHxa0MwV3hiqLwT8FpgV8i+D2CsHw/XDSCWAWr4SP+rr+2aQOY6YrIw/opn634NvC23/+Z38wliaeLwBLEoxyFrxo+7oPCsqGhAWfjjCHdA+3t7YUCNS0tDb6vrP+a6HzNyrmRq6CmZzjT0MHdKxfNUial3/nQn8StDIEdmCuAK4pmZ2fn5ORgsMFPDFTmpaWlVWOCKh1aWHACQ6PViUzp7mhSSJoJXQRIfUr0PqeZqcciRyNXbW0tfmVl/UjXroKv9bSf/vZvvGF09N7brodtLymzPL6WHZVbgOMqUEVFRZAMVVXVdYa039zczO5gBQKBlpYWcYcyoLujSQHSIORczUh3PzgvE1wKQiqT+WhBfGsOcOIW7Q1Grc8ta86Fa8Kanz0hmtoaNsGGSy8tE02G4JbgJKxfvx4jCqoDto6NoeBHB4diKNFx+iZvrtLd0aQAb8tR+BXPiIo9njYj3QPVAt5ghPwgLrpy/zc/DabrN94nbvXYfbeDaeU1/y6aDIEdmBPo6enB+1JQhUJZrusTA0KhEKRQLFDZ/y5zRqByNCkkzYTOAX718TuHN/p0fUSIHI2RIA9ghbZx40bOtOu3906frMw948pBzjA6WvW5yFqi5TU/5w1GYkflBNjZgOJclRSfZgB+zvB/xyUZdX0YvNL5LBvUK/MhSDhIg5BzNSNuP1h3WR03IL61LsB3Gu+X8s8Pj/eYUTb+uOXYyPtbHXi5ff4sZfqc059+5aB2PybBuXB1CjgbvMG62OLE5eXlvC0REk8XgSXwqhzFlYmg7lJVlbcZSfdARQgGg/AWxcXFnOmlp3516uyp6VNP+vI3ftDR2Q36xYN3n5t3ypSps2sfahsR9mMG2IHZA8jYiqvrNEEcQl2alpa2detWmU/cgORQ0kzoENgafaIpNkSOxrTy8vLgglO4vTHStbPl4hWLFY3mLF7R2LJzrM+MNbGjsgdsAanOzk6Zjw1oa2vDh/7ejo0i8B6kQci5mhHzVFUVf/hxCJLWZAjiW8cA7ABQVlYmmkZHQ3teePqhhx4KPvTQU399IaS3uXmwLTaMEBeQcle4NHdCppDSSjxdBJbAk3IUn+ZVVFTwBjM63Fd316aqqv88JDliLahjs3qKJnchcmC2AAfUr1q1SjQ5B4hwvNkT5ymkOCA5lDQTOgHsloXP02U+Mhg98FLuyScoytKeyHEZC2f1bGmJDCT3SHhs9gDSIPxGeLdyRvynkCJwHaRByLmaEXqyDsqsxRJwQYjtMQB7n+BwdZmPc7AnLkI8kjbOEyLxdBFYAvfL0ebmZrxO4w0mxYJQcsQcqNHrT/iiezolaeTArAPODGCmVhwJDfe9+Yaqqq/39Bx674iujwyw4l2/fr1oig+QHEqaCW0DdmdpbGwUTWbAajnKJudWx56Auy48NquATzIhTfX1Gcxz0/ar+z5RcP68WZGuMBnTpi0JfPi7//nI0LDZ0Y8xxkYRJAWMy4TYalu4OQah7lhBEfr3vPytypuWzZ0Lm8zKXXp9+c072x5bONdCOQrCJ9eqqoomV0DWHhtwlio4NtHEYCR05MffiFzTnn5O/h131gWDwc13fuejgaXQUnzjN3HQlbiVCLm5ubAJ652r6+MRhEmOFcmEfJtEzFMG+Ap5KScnx8xT6d6Xdn5o8Snw7ZmembVoUW7uwoUnzZ4xbfr0yZMnYTkq25AD7NKN0yLKfByCDVVVVSnRJxO8QaO2B2umTplUWPrvb71zmDUODe6/7oLTJqXPqP/d3zW+sYTPKoLRNWfiLPFcEViFSCYUW52AEh38pmvSwvDgW9fkRwbgXnzdV5/5x6uhUHjk6HCP+vyDd39rVmQFhePXhLLNtYBdZ+BLL5qcA3u1ChiEGBj6PkcO/suHT1VmLe7qO34RyEzYA7bgc1U6W+mB8Xt5BmGSY7lfjpoMwsf/61vgufSi0v6hkNZk9e7o6PgglPk4AVl7bMCRR7omhL27mk/KUM5dc4toeld9ev7sKdPOvkI06YIavTsVu/T1CMIkx3K/HDUXhMfWf2IFeP6oSRjmq7k7qrehDrAgFE1ugQ3hdRrfqlH7I3WQ8adlzs4VtOjU+WmTI2Mf+W0kUjVBGGeJ54rAKiSoHD3yxgWnZivK7Of2H3+u8L5p/CMK/c3Hgz/L0dxoEOqaEHCQ8fy8D5fJtOEucStdUCkTJrMSVI7KIy1lylHDIHw6mgkvvuE7oskqqBSEySz3y9GSkpK0tDQ2zE/XM3zotbPmZylKzj/fE0zWy1F8Jo5jFGQ+DsGGMAj5Vo1ef2b7iRnKrLOvGB7hTValUjmazOB+OVpm5jnhsYNFSyNjC7Z3RuZKGWeSJ0kZaJ8TynxsA3u1CnhjJsY4o2NH+i4/62RFSd/a8jeZj0lgffdEk9cQJjmW++UoG17EWnShZv2V4HbDhvuOjTcd2bvr1JOmmy9H+/r65s2bZ3XlJksga48NZh4b/PkXdZlTlZlzlvzyfzuOaUxH3+1/LHh3xTd/oruVCGbeyyMIkxzL/XIUClEoRwOBgOighVf/8uiJ6WnpJy7c/MiTA0eGoWXo8OA/nvr9Jy8+azJ8oUyXo1CFgjdUpKLJRbAhM+O5Ro4NN/6wMitz6tRpJ6z6eNHtt99edccdXym/YcniU9InTbryplp+A4mKi4uV6Fw+vMF7ieeKwCq4X46GNZdDoul9OHb0nls/BW6T0qac+eGVUFJ+cPlZU9OUD61cNSszw3w5ypKAaHIF2KtVUE3fLHl515Nf/383fHBZ3rRpijJ58smLz1jzmbJ7/+fRV/dGOp3KttKC4U0g7yBMciz3y9HwWGDU1NSwFgkM37/plnNOX5CWpqRlZp5z/kV33fer4UOvr11zRUHBDfv1PnIOtMvfynycg6w9NkB5DEWyoulZLvq4AnD5rUTHDYumOECY5Fjul6PhsRIRhxfpemrh8KEDu3eru9944/DwUWzRddMFHDaFE7rJfFwBe4JaVNE8wPRIOKsdLvMUf4nnisAqGBWNtoANL2ptbZX5uAI4A6ftYVNmgL3agN7eXiX61FQ0uQheD96PDWGSY3lSjgK0tLRgjQQVI2eKDdoPODawceuiyV2QtZsB9jMhmlwBXGWgtLRUNMUHwiTH8qQcRcDvn43VMHUbOdDOcSTzcRFsC2oBXEmKTTznoiD72VhlwF2J54rAKnhSjiKwEd8xViO0DTiCDq4G2UJroo8rwF5tAz61X7t2rWhyCDihVkKe0TMIkxzLq3IUQTsxpsyHA91PmgOo7pTowkye3hRlIGs3Cew2KQ471vWxAXg/JlE3RRmESY7lYTkaji4kxPKAmbH2CLqNDOBSEGeA9/qujxYcCo85Kyurs7OTt9kSXg/n5OS4tUPbEs8VgVXwsBxF6O3txUXnra4Mows4pTxmFZmPu8BeHUJ1dTXL3jIfk8BOQkNDg8wnbhAmOZa35SgCWxUMaif2yy1z1v2kEeB7jKvz4ZTyuj5egKzdKmBxDnG4detWmY8haE+CzCeeECY5lrflKIOenp7S0lIlutI1JLHYC1yKjV1dXdrNdX08BVcExTnEIdbS5eXlODmaeemehIRLPFcEVsHzclQL7Fd82bJlbGowmTMCFG/r1q3LyMgwmUhdB/bqFuBqShhLFRUVEIqiDwdwEmpqavAkKGNrj8uc4wxhkmPFoxzVQkdHB66aBoJrxbKysubmZu3gQ3hVVRVaIGLhMhI9c3NzsSeq+CWIA8jabQMUAuwkKNFhX3V1dfAva32GhoagpbGxkZ0ECEL4PdqwYYMSnW9bd8/xhzDJseJUjnLQ3t5eXFycnZ3NvojHZziKCu86gKBsgz/hCqq/Xxj7G1/wQnASoDqVnYScnBzWDpeRVVVV+EReVVU0wc8Zv8dESDxXBFYhruUoB1BTwS895AHsW8ME1VpklqMNG3CODNnm8QH26hHASYCMB5kNZyQQTwJY2W8QbtXQ0KB48/TfBoRJjhXvctQQtB+wT0DWnihgT//pEUVqKDHlaGzQbUws+E34sB5CkXVFSpTEc0VgFRJZjiYFsFe/QVFREcRhfX29aIonhEmOReWoMcjaEwsdHR340CIhizExCJMci8pRU+BP4TQiseeS8lriuSKwClSOGgB79SHgdI9ZWVlwiSjz8RrCJMeictQYZO1+AFybsbCwUDTFB8Ikx6Jy1BT4WYFAQDuwK84SzxWBVaBy1ADYq2+BDXEWTXGAMMmxqBw1Blm7fwBHV9TU1IgmryFMciwqR02Bz4UzPuXm5vb04OoB8ZN4rgisApWjBsBefQ7r1q1TEjH3YZjkWFSOGoOs3W+QkFmAwyTHonLUFCSF6urqlOjQZ97gmZ7dtlk7/IrT5m3Popt4Pgm0QOWoAbBX/0N/fz8OCmtpaZH5uAs7g5HZqxYsCZTp6dc7IlNakQxF5agxyNp9CLhkL070KvNxETAIL7+xKkxyICpHTUGyiE306vVSUChtEIonjcAkUDlqAOw1WQCXgsrOzo7DZFCUCV0RlaPGIGv3LcRtMigKQldE5agpSC6p8ZoMCoNwxcfWbPnhD6EA/u5ddz3ySMtrvftHRiLnTTyNBLpA5agBsNfkgvhMBoVByGn67HllG2oODB5fpJlkKCpHjUHW7meIz2RQ+7pf3vHUs28dOhQJuFDorb3qA1vuOnP+ifC+F9/wTYpCk6Jy1BQko+IzGZR4rvY891hO1jRl8tTfdB6U+RBogcpRA2CvyQhxmAwqrKNjXyxaCu/7jS2/5y0kPVE5agyydv9DHCaDCuup6sbL4U1v+l6QN5D0ROWoKUheiZNB9ff3t7a2QntxcbG2q2dpaSk0wjWkpeWixHM1OnrsS1dGVsL75k//KJgIdIDKUQNgr0kK2smgcIkriDd2J1NX4Lx69WqcPErcIQdhQYNvdJyePUNRZj3+Sj9vI+mJylFjkLUnC+BkULheshJd3amgoCAYDG7btk3rDFEHjWvXroWgRc9Vq1ZBzhR3iNCnPlVy2XU7n3vx2MhIeEyD+3bfcPnZijKp6MbvsUZSbFE5agqSV6FQaOvWrRhUuEiw4eh7SJ5NTU35+flKdGGs8vLygYEB3ikcPrB754JJyrTpmSvO+9jNlZVQylbe9PnTF8ydlDblouL1PW8fEU8jgS5QOWoA7DUZAa7usD+3El0FkVvdyRAaGxvZoq7i1KahIwOPNz90443XfySweGZ6OrjNOGHW+UVr7n/o0UPv0TNCC6Jy1Bhk7T4HiEAsQSEBwtWgro8hsPVMIRq5ZUwRwiTHonLUFCSdoOZcvjxyixJCCMpL3mxRtbW1UJdCHEI+5EziuSKwClSOGgB7TS7AK7qSkhK3RvdCHCrRG6c4QoqZwiTHonLUGGTtvoX169cr0XuboskJ4F1W2K322jJMciwqR01BEgm7jObk5HR2dvI2x8I5bMrKyliLeK4IrAKVowbAXpMCvB48ATkQnyKyOz1hkmNROWoMsnYfQnl5Od6MEU1uAT51ZHNJhUmOReWoKUgKqaqalZWVmZmp+2zdLbG5pJqamsJ654rAKlA5agDs1f+AU8tUV1eLJncBLzvz8/PxT5JDUTlqDLJ2v0FeXl5GRkZHR4doch3YlPthkmNROWoK/K9t27ZBdiouLuYN3gin3GcTuoX1ThqBSaBy1ADYq88BO5d5dFNUBMiBkAkhH4ZJjkXlqDHI2v0DQ0NDgUBA7M7iKWCnHLEjG8mqqBw1BT6XqqoQDwUFBbzBWCNv739r925V3bOn78DbmoGBxsIx+8FgEP8UTxqBSaBy1ADYq58Bn92tW7dONMWAwwf33HLTpxedfNKkSYqSnn7ayqJ974ZkziK0t7ezZ5IkJ6Jy1Bhk7f4BbVKS+XBw7Eh/WeHZsNVF15Rt+cl/Be+7b8M3Nx0YtBCEqv30SxonKkdNgc9VWVkJ8bBt2zbeINfLf/rZCVOUFf/yxaGQlRpUo56enoyMjNzc3P7+yFwy4kkjMAlUjhoAe/Uz4NxNuiYZNG2+BTb5+tZm0WQeIA3CTlRVDZMciMpRY5C1+wcsBeFI6MizTz95+42ReYFvvL2ubUy4eoRsK12gIHRFVI6aAp8Lg5BvlejooTfPy5ulCPrtC4d4VyNpg1A8aQQmgcpRA2CvfgbbmfD6mzdRJky4qBw1Blm7f8BSECI0bCqDTW7dsl00mQcKQldE5agp8LlwTidLI5hYEPIG0wqFQthpRlXVsN5JIzAJVI4aAHv1M9h4Tug8E6rR54Q4ujdMciAqR41B1u4fSGAQ0sN656Jy1BT4XE1NTRAPq1ev5g1yOS9H8U3Zek/iSSMwCVSOGgB79TOomqQk8+HAeSbkOnCTbIvKUWOQtfsK2I1K0aQLzoMQb8nitGskJ6Jy1BT4X1AWQkjU1tbyBokclqPt7e1paWmBQEA8VwRWgcpRA2CvPgft5EsyHy04zIRsUqkwybGoHDUGWbvfAKfH1l07SQSHQcgmlQqTHIvKUVOQFMLJl7Rz1MfQQH+fqqoHDx3mDSYUDAaVsUmlxHNFYBWoHDUA9up/EOeoF32cA5tpHy4LsZ3kUFSOGoOs3YfAzVGv6+MQuJn2wyTHonLUFCSL2Bz1DQ0NvM0NdXZ2cjPti+eKwCpQOWoA7DVZAG+TejQVN5a72pn2wyTHonLUGGTtvoX6+noIlby8vN7eXpmPVYD6tqSkBHZbWlqqNYVJjkXlqClILkHA4ITcy5cv7+np4c3WFWOH4rkisApUjhoAe00uYIkLwgan5RZ9zAPuSje1hkmOReWoMcja/Q8YPMrYbIi6PrGhs7MTrwNlwRwmORaVo6YgSQX5sKqqKiOq4uLi9vZ23kMuCLny8vKsrCy8DpSVteK5IrAKVI4aAHtNXujo6IBKElMiXNpBVhR9tADhV1FRgeGXmZkZe9XRMMmxqBw1Bll7ckEwGMSeLqiysrK6uvcnHQVBsEEjFp8ggI0bNw4MDMh2iBAmORaVo6YgNQQR1dDQAHVpdnY2i0ZOkPry8/Nra2v7+vr47fUknisCq0DlqAGw11QCKDgh9UEmLNNow4YN0NjV1SXbShfCJMeictQYZO0E+EpyKCpHTQFJJvFcEVgFKkcNgL0S6EKY5FhUjhqDrJ0AX0kOReWoKSDJJJ4rAqtA5agBsFcCXQiTHOv/AA6WNHZ2HRSXAAAAAElFTkSuQmCC>