核能電廠的升載過程，須兼顧經濟效益與機組運轉安全。經濟方面的考量應盡速達到全功率運轉；至於安全方面則是在運轉過程中，應確保核燃料在各種運轉狀態下能維持它的完整性，並且必須符合各項安全運轉限值，包含最小臨界熱功率比、最大線性熱產生率、最大平均平面線性熱產生率、燃料封套值、功率震盪等。目前這項工作由核子工程師利用爐心監控系統，規劃升載時的抽棒、等待建立氙濃度的時機與觀察運轉限值的餘裕情形，並於啟爐前完成事前規劃的工作。
本研究的目的是使用蟻群最佳化演算法(Ant Colony Optimization algorithm) 來搜尋升載路徑，並利用SIMULATE-3的功率搜尋模式(power search)來計算爐心狀態。演算法中，元件解的集合包含所有可能的升載動作(抽棒和增加流量率)。將路徑搜尋過程中的熱限值、功率震盪、最大控制棒負載線、封套限值等項目，規劃成品質函數中的懲罰項，運用啟發式訊息(Heuristic)排除建立解的過程中不合理的動作選項。利用SIMULATE-3計算升載路徑的爐心狀態，接著求得品質函數的計算結果。根據解的品質函數值進行費洛蒙濃度的更新動作，直到程式收斂至一最佳解。
開發完成的程式使用兩個週期進行驗證與反覆路徑搜尋，其結果顯示達到目標。

During power ascension in boiling water reactor, both economic benefits and operation safety must be considered. For economic consideration, it should bring up the power to the full power level as soon as possible. As for the operation safety, it should ensure the fuel rod integrity under any operation condition and thus have to satisfy all the operation safety limits, including minimum critical power ratio, maximum linear heat generation rate, maximum average planar linear heat generation rate, fuel envelope, power oscillation, and so forth. For the time being, this task is designed by nuclear engineers who use POWERPLEX-III to figure out control rod withdrawal, xenon waiting, and watching the margin of the operation safety limits during the power ascension, which must be finished before start up operation.
The goal of this research is to use ant colony optimization algorithm to search the power ascension path, in which using power search mode of SIMULATE-3 to calculate core status. In the algorithm, solution component set contains all the possible action, i.e., control rod withdrawal and core flow rate increment. To consider the thermal limits, power oscillation, maximum control rod line, envelope and so forth during the path search, those terms were formulated as the penalty terms of the quality function. The heuristic information was used to eliminate the unreasonable action when constructing solution. Using SIMULATE-3 to calculate the core status along the power ascension path, and then the quality function was calculated. The pheromone concentration was updated according to the quality function value, until the program converge to a best solution.
The developed program was demonstrated by two cycle and the results show that the goal was achieved.

1.“ATRIUM-10 核燃料預先調節細則 第2版”，台灣電力公司，
2008
2. 楊昭義、歐陽敏盛，核能發電工程學，水牛出版社，1997年
3. Mechanical & Nuclear Training, General Electric Company,
1980
4. L. S. Tong, “Principles of Design Improvement for Light
Water Reactors”, 1986
5. 李綺思，「結合基因演算法及類神經網路自動搜尋沸水式反應器
升載路徑之研究」，國立清華大學工程與系統科學研究所，博士
論文，中華民國九十六年
6. C. D. Wang, and C. Lin, “Automatic Boiling Water
Reactor Loading Pattern Design Using Ant Colony
Optimization Algorithm”, Annals of Nuclear Energy, 2009
7. C. Blum, “Ant colony optimization: Introduction and
recent trends”, Physics of Life Reviews, Vol. 2, No. 4,
2005
8. M. Dorigo, V. Maniezzo, and A. Colorni, “Ant System:
Optimization by a Colony of Cooperating Agents”,
Systems, Man, and Cybernetics, Part B, Vol. 26, NO.1,
1996
9. K. Socha and C. Blum, “An ant colony optimization
algorithm for continuous optimization: application to
feed-forward neural network training”, Neural Comput &
Applic, Vol. 16, No. 3, 2007
10. T. Stutzle and H.H. Hoos, “MAX-MIN Ant System”,
Future Generation Computer System, Vol. 16, No. 8, 2000
11. A. P. Engelbrecht, Fundamentals of Computational Swarm
Intelligence, WILEY, England, 2005
12. Simulate-3 Manual, Studsvik Scandpower, STUDSVIK/SOA-
95/15 Rev 2. 2001
13. 沈芝慎，劉祖亮，洞悉UNIX入門篇，和碩科技，台灣，中華民國
八十四年