在現今社會，隨著生物科技的進步，越來越多與生物科技相關的產業因應而生。政府1982年即將生物技術列為八大重點科技之一。在這些生技產業中，由於現今出生率降低以及經濟條件改善，臍帶血儲存—臍帶血銀行成為迅速的成長的產業之一。而隨著市場全球化的趨勢，台灣的本土臍帶血銀行，希望藉由擴展市場來與國外競爭者競爭。而為了提升競爭力及創造更多的利潤，臍帶血銀行需要更有效率的擴展它們的市場以及儲存顧客的臍帶血。為了達成這樣的目標，臍帶血銀行不能僅專注於臍帶血儲存技術的發展，也需要在經濟效益的觀點下決定實驗室定址與運輸途程的安排。由於臍帶血銀行的不穩定需求及有限的運輸時間特性，本論文主要討論兩項臍帶血銀行的實務上的問題：實驗室的定址問題以及臍帶血運輸問題。基於此兩項問題互相間的影響與關聯，本論文使用基因演算法（第一階）及禁忌搜尋法（第二階）結合所完成的二階演算法來討論臍帶血運輸系統規劃，並達成兩階之間的共識。在本論文的實驗中，我們以Solomon的含時窗限制的車輛途程問題例子著手，運用發展的二階演算法以得到其最佳解。並且，本論文利用改變模型參數進行敏感度分析來確定穩建的參數模型組合。其實驗結果證實本論文發展的模型可以解決在臍帶血銀行中的實驗室定址與運輸規劃問題。

Nowadays, as the progress of biotechnology, more and more products associated with biotechnology emerge. Since that, Taiwanese government put a huge effort to biotechnology industry from 1982. Beyond this industry, cord blood storage – Cord Blood Bank (CBB) is one of the businesses, growing rapidly since the lower birth rate and the better economic condition now. As the trend of globalization of market, local CCBs, such as those in Taiwan, aim to extend their market to compete with the competitors abroad. In order to be more competing and make more profit, CCBs are required to efficiently expand their market and store the cord blood from customers. One does not just focus on the development of technological innovation, but also require determining site locations and transportation routes from the perspective of economical benefit. By considering uncertain demand and limited transportation response time in CBB industry, we aimed to discuss two research issues of the CBB practice: Laboratory location chosen problem and cord blood transportation problem. Due to the interaction of these two problems, this study proceeds with an approach using a two-stage algorithm combining two heuristics - Genetic Algorithm (GA) in stage one and Tabu Search in stage two which discussed as cord blood network transportation planning to make a trade-off between these two stages. In our experiments, the set of Solomon's VRPTW instances are attacked and found out for their best solutions by the proposed algorithm. Then, we have examined the robustness of the proposed model by changing model parameters and algorithm parameters. The outcome of our experiments has justified that the model developed in this study can solve the location chosen and transportation planning problem in CBB industry.

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