本研究歸納的結論如下:
1. 針對 DDBAP，本研究以 Imai et al. (2001)做為比較基礎，成功導入啟發式解法 -螞蟻演算法到此問題上。將演算法的求解機制納入船席指派的概念，包含船 舶抵達時間的資訊，以及過去的求解經驗等都將一併納入考量。能有效提供給 碼頭營運商船舶分派的優先順序以做為船席指派之用。另外，透過本研究自行 開發的 GAR1 以及 GAR2，將螞蟻演算法提供的指派順序，轉化為相應的船席 位置，碼頭營運者即可得知任一艘船須在何時、何處進行指派作業。
2. 進一步探討本研究的迭代效果分析，可發現在不同的試行結果之下，不僅末代 的平均目標式值能顯著地低於首代的平均目標式值，而迭代之中的最小目標式 值也同樣低於首代的最小目標式值。此結果說明螞蟻演算法能發揮功效，透過 回饋機制，使得求解系統產生更為優化的求解次序，並強化求解品質。
3. 比較 GAR1 以及 GAR2 的求解效能，本研究透過規模大小相異的例題，進行 比較。可發現在小範圍的例題中，GAR2 與 GAR1 的求解能力相去不遠。但在 範疇更大的例題當中，GAR2 的尋優效果便可顯著地提升。一旦問題的複雜程 度越高，更能彰顯 GAR2 的求解功效。
4. 本研究透過螞蟻演算法搭配 GAR2 的求解機制與 Imai et al. (2001)進行比較，
可發現無論問題的規模大小，本研究的求解能力都較為卓越。此舉顯示本研究 在處理船席指派的問題上，的確有其代表性，也可供其他欲投入螞蟻演算法到 船席指派之學者作為參考。
本研究提出的建議如下:
1. 本研究所探討的問題情境仍可再加入更多管理意涵，例如時間窗限制、船舶的 權重因子等要件，可繼續研究螞蟻演算法在情境更為複雜下的求解能力。
2. 可進一步把螞蟻演算法的概念導入連續型的船席指派問題，觀察是否能有更好 之結果可展現。
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簡歷
中文姓名：陳儀安 英文姓名：Yi-An Chen
出生日期：民國 74 年 11 月 4 日
聯絡地址：桃園市經國路 555 號 5 樓之 1 聯絡電話：0939-672216
E-mail : yian41@gmail.com 簡歷：
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