由於經濟迅速成長，人口過度集中於都市，使得都市土地價格飆漲。對於建商而言，土地成本的不斷提昇，迫使其設計或興建更高的大樓，以增加建築物使用面積，新建築物越來越往高層發展已是必然的趨勢。對於建築物內複雜的垂直運輸交通需求，必須仰賴一套完善且有效率的電梯群系統來加以解決。
一般業界規劃停站服務策略之方式多利用簡單的數學規劃，並對特殊使用樓層增加派車服務。但隨著電梯的運行，旅客的流量資訊隨時間不斷的變化，簡單的統計推測已無法滿足對電梯系統的即時、彈性及多目標需求。
因此本研究透過優化乘客待服務等候時間(Residual Waiting Time, RWT) 建立一模擬電梯群控系統，進行隨乘客呼叫的動態優化派遣以提升系統效率，且引用【Elevator Group Control with Artificial Intelligence, 1997】藉流量資訊模糊推論界定樓層間運輸之交通模式，並參考公車停站策略建置適合電梯的停站策略。系統於不同交通模式下模擬所有策略組合，依不同之電梯群服務指標遴選適合的停站策略。最終，本研究建置之系統與一般系統於不同交通模式下比較服務效益。進而應用在不同交通模式時，能及時提供適用之電梯群停站策略組合。

Due to the growth of the Taiwan’s economy and excessively concentrating population on the city, the price of land in the city rise wildly. For building dealers, the continuous raising land cost forces them to design and build those higher buildings for increasing the useful area. Therefore, it’s a consequential trend for those higher and higher new buildings. For those complicated vertical transportation traffic demand in the building, we must rely on a set of perfect and efficient elevator systems to solve.
Generally, lots of industries take simple mathematics methods for planning the strategy of stop serve way and increasing the service of sending cars for some special floor. But with the operation of the elevators and continuously changing of the passenger's flow information, those simple statistics inference already could not achieve the demand of immediately, elasticity and multiple goals.
Therefore, this research build an elevator group control simulation system by optimizing passenger’s Residual Waiting Time to process the dynamic optimization sending service following by passengers called out for improve systematic efficiency. Fuzzy logic rules inference of flow information used in【Elevator Group Control with Artificial Intelligence, 1997】 is used to define the traffic mode which can transport among the floors and refer to the strategy of bus stop for building a suitable elevator stop point strategy. The system simulate all strategy composed in different traffic patterns and choose some suitable stop strategies by different elevator group service targets. Finally, the system built in this research compares the benefit of service with general system in different traffic modes. Furthermore, it can apply a suitable elevator stop strategy composed promptly under different traffic modes.

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