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  • 學位論文

利用杜鵑鳥搜尋法求解設施位置問題

Using Cuckoo Search for Solving Facility Location Problem

指導教授 : 巫沛倉
共同指導教授 : 江育民(Yu-Min Chiang)

摘要


由Weber. A於「工業區位論」(Weber, 1909)一書中從經濟面向提出區位因數決定生產場所,將企業吸引到生產費用最小、節約費用最大的地點的相關問題後,企業如何於適當之地點設置工廠、配銷中心、售貨地點,或是一切與生產配送分佈系統有關之問題即成為各大小公司企業發展的重要課題。電子商務的興起帶來數量龐大的訪客流量與巨量訂單,也產生更複雜的配送網絡需求,與供應端有關計劃、供應、製造等相對應的變化,除了增加將產品送達消費者的困難度,更重要的,對於龐大的商品訂單應如何消化產製後集儲運配,更是企業所需面對的重要課題。對於設施選址問題有許多的研究方法,許多學者提出各種不同的模型企圖解決不同理論與實務上的選址問題,服務數量受限制的設施選址問題具有兩個限制端:提供服務之設施與接受服務之顧客,兩者均有服務數量上之限制,如何在提供服務之設施能量上恰好滿足接受服務之顧客需求,則相較於服務數量不受限之設施選址問題上複雜許多,因此一個能夠於合理時間內求得較佳解之相關演算法即顯得相當重要。杜鵑鳥搜尋演算法自從2009年經由Yang X.S.j提出後已在許多工業應用上獲致不錯的成果,但大部分應用在連續最佳化的問題上,對於離散最佳化問題的著墨較少,本研究著眼於杜鵑鳥搜尋演算法具有選用參數少、搜尋路徑優、尋解能力強等特點,於傳統使用之啟發式演算之外,利用杜鵑鳥搜尋演算法之特點,對供應鍊網絡中設施選址問題求得最佳化的結果,主要是以設施選址問題中的服務數量受限制的設施選址問題為探討對象。 經由本研究實驗之結果證明,杜鵑鳥搜尋演算法在服務數量受限制的設施選址問題上亦可獲得不錯之成果,於本實驗所使用之公開問題集中均可有接近最佳解,並其解算時間亦在令人滿意的可接受時間內。惟因本研究模型設計之限制,於求解空間及演化上仍有精進之空間可做為後續研究之參考。

並列摘要


The logistic network of an eneterprise is more important than ever. Since Weber. A proposed the standortsfaktor, as Weber called in his book "Uber den Standort der Industrien.", or location factors by M.C Green Hut, how to deploy the factory, sales center, or any facilities that related to productive distribution network becoming the most agenda to a aggressively corporation. The facility location problem is more important with the growth of modern company that deal with B2C or B2B. So many specialist work on the problem of more efficiency of a dis-tribution network, they propose different algorithms to discuss on such problems, including Genetic Algorithm, Particle Swarm Optimization Algorithm, Colony Algorithm, Tabu Search, etc. In 2009, Xin-She Yang and Suash Deb proposed a new heuristic algorithm that simulates cuckoos breeding behavior and got a lot achievements in different engineering fields. The Cuckoo Search has less parameters, better search route, and strong search ability. This research use Cuckoo Search to solve an Capacitated Facility Location Problem. For the result of experiment, we have solve the Capacitated Facility Location problems with better solutions within satisfied solving time. In the future, the model of this research should be improved to get better nest and search space.

參考文獻


藍俊雄、邱誌偉、胡鴻慶(2007),整合式多期規劃供應鏈模式,科學與工程技術期刊,3(4),87-98。
游弘宇(2014),探討國際物流中心選址決策-以網路服飾業網路服飾-T公司為例,台灣大學商學研究所未出版碩士論文。
Adnan, M. A., & Razzaque, M. A. (2013). A comparative study of Particle Swarm Optimization and Cuckoo Search techniques through problem-specific. International Conference of Information and Communication Technology (ICoICT).
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Avella, P., Boccia, M., & Mattia, S. (2013). A Branch-and-Cut algorithm for the Single Source Capacitated Facility Location problem.

被引用紀錄


蕭翼遠(2016)。應用演算法於醫院選址問題〔碩士論文,中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201600874

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