「區位---指派問題」在運輸問題中被視為一重要的研究問題。因為人類活動需要在一定的空間佔有特定的區位，而距離在決定這些區位中佔有極大的角色；由於空間是由點線面所組成的，在相同的空間結構裡，常因活動與需求的不同產生不同的結果，因此，區位---指派問題在不同的結構理會表現出不同的特性。其中的p-hub中心問題被廣泛的應用在航空、通訊、郵件送發問題上；回顧文獻對於p-hub中心問題之求解，已有釵h啟發式的方法被廣泛應用求解最佳值，包括基因演算法、模擬退火法、Hopfield network、Branch and Bound Method等等；而這些方法都是預先決定服務中心的數目，找尋最佳的區位，並且使得各需求點的總加權距離最小化。
本研究針對顧客及服務中心數目已知的條件下，提出利用類神經網路中的自組織特徵映射法於對應問題之求解，運用神經元的自我學習弁鄖荍銗X最佳的服務中心區位，並利用實驗設計的方法，檢定學習率及學習次數是否對於求解的速度和解的品質有顯著影響。
本研究應用自組織特徵映射求解p-中心-中位問題，p-中心-中位問題亦屬於區位-指派問題之一環；於本研究中，將於第一章概略說明p-中心中位問題及自組織特徵映射的發展背景及研究動機；於第二章探討過去對於p-中心-中位問題及自組織特徵映射相關文獻；於第三章說明如何使用SOFM求解p-中心-中位問題；於第四章展現先行初步計算之結果。

「Location-Allocation」is a important research area in transportation problem. Human activity need specific location in space, and distance is very important in Location-Allocation problem；Space was composed of points, lines and faces. Different activity and demand generate variational result in the same space structure. Therefore, Location-Allocation problem show different character in different structure. P-hub median was application wide to air, communicate, post system and etc. Much heuristic methods was applied to find optimal solution in p-hub median problem, include genetic algorithm, simulated annealing, hopfield network, branch and bound and etc. all of these heuristic methods were know number of hub previously, and sum of nodes demand must be mini-sum criterion.
This paper solve p-hub median problem with SOFM in number of hub and node were decided. This concept is using self-learning of neurons to get optimal location and cluster. On the side, using experiment design to check parameters in algorithm whether significant in solution quality and efficiency.
This paper is organized as follows：Section 1 introduces background and motive of this paper；Section 2 presents literature related p-hub median problem and SOFM in the past；Section 3 gives p-hub median problem and its mathematical model, In addition, introduces proposed method with SOFM applied to p-hub median problem；A case study and experiment are reported in Section 4 and conclusion follows in Section 5.

中文摘要 I
英文摘要(ABSTRACT) II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VIII
第一章 緒論 1
1.1 研究背景與動機 1
1.2 問題描述 1
1.3 研究目的 2
1.4 研究架構 3
第二章 文獻探討 4
2.1 軸輻網路以及折扣率問題 4
2.2 區位-指派問題（LOCATION ALLOCATION PROBLEM，LAP） 5
2.3 P-中心中位問題（P-HUB MEDIAN PROBLEM） 7
2.4 自組織特徵映射網路（SELF-ORGANIZING FEATURE MAP NETWORK,SOM,SOFM） 11
第三章 研究方法 16
3.1 問題描述 16
3.2 問題模式假設 16
3.3 應用SOFM於無產能限制單一指派P-中心中位問題中 17
3.4 測試資料 29
第四章 實驗設計 30
4.1 兩水準因子實驗(高低因子) 30
4.2 變異數分析 37
4.3 簡化前後比較 70
第五章 實驗結果 72
第六章 結論與建議 76
6.1 結論 76
6.2 未來研究方向 77
參考文獻 78
附錄A AP座標資訊 84
附錄B 各問題最佳值 86

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