近幾年來，隨著科技的進步與變遷，人們的生活品質提升，造成人們越來越重視旅遊導覽上的參觀品質。因此，在現今的學術研究上，旅遊導覽系統部份亦成為重要的研究領域，截至目前為止已經有許多人在專研旅遊導覽領域，但是這些研究主要都著重在個人旅遊導覽系統或是針對多目的地去做壅塞控制的排程，大部分研究探討的使用者身份都是以個人為止，很少研究考慮到一般在現實狀況下，觀光遊客都是成群結伴的或者甚至是由好幾台遊覽車帶來的，所以我們提出一個推薦機制，為了要解決多群體在多目的地上的壅塞減少排程議題。
為了解決多群體在拜訪多目標地時，在同個地點裡發生壅塞的狀況，造成參觀遊客的觀光品質降低，我們嘗試依據壅塞狀態，向每個群體推薦適合他們自己的下個最佳地點，將多群體依照不同時間點分散到不同的地點，以減少每個地點因為壅塞所造成的等待。本論文使用螞蟻演算法的費洛蒙機制來記錄遊客的常走路線，當某群體從入口處進入到園區中時，會收到十筆過去遊客常走的路線，當此群體走在一定範圍內會收到景點處的訊號，此時，我們提出的推薦機制會由一台超級電腦運行，其會根據這十筆過去遊客常走路線加上目前群體附近景點的壅塞程度，最後依照各群體的狀況去推薦下一個最適合此群體的目的地，主要的目的是讓每個地點的壅塞狀況減少，以達成多群體的平均等待時間越少越好的目標。

In recent years, tourism navigation systems have become an important research area because people have focus on the quality of the tourism. There are a lots of researches on the tour guiding have been proposed so for. The researches are interested in personal tourism navigation system or congestion-aware scheduling method for traveling multiple destinations. However, those navigation systems mainly focus on the guiding for personal use. They don’t consider tourists as groups. So, we propose a recommend mechanism which is focus on congestion-aware scheduling method for multiple groups in traveling multiple destinations.
In order to reduce congestions in the visiting multiple destinations problem for the multiple groups, we try to recommend the suitable next destination for groups. We need to distribute congestion over space and time. In this paper, we propose a novel multi tourism group routing path mechanism that will discover historic sightseeing routing path and recommend the suitable tour path based on multi tourism group and multi sightseeing. Our goal is reducing the average waiting time for the group by recommending the suitable tour path.

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