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  • 學位論文

應用基因演算法於轉機組合最佳化之研究

Optimization on flights combination using genetic algorithm

指導教授 : 張淳智

摘要


近年來出國觀光旅遊是深受國人們喜愛的休閒活動,自助旅行也是受歡迎的出國旅遊方式之一,但是如遇天候不佳或是航班誤點時,又該如何選擇可替代之航班?因此本研究主要是針對考慮時間與成本兩個目標選擇飛航班機到達旅行目的地。 本研究使用基因演算法以單性生殖的演化方式,發展出一套演算法,並針對亞洲地區求解出兩國間航班的組合最佳化,使用柏拉圖的受支配個數法得到柏拉圖最佳解之前緣解集合,而研究結果顯示本研究所發展出的演算模式設定在母體大小50、演化代數800、突變率為0.2時可得到最佳化的解集合。 另外本研究發展之演算法除了應用於旅遊航線路徑規劃外,也可應用至其他不同的研究領域,像是國與國之間的海運承攬問題,或是貨物裝載以達到最佳載貨量之相關研究,用以達成現在這時代所講求的效率與品質兩者兼具,這也是目前國際貿易業者所要面臨之問題。

並列摘要


In recent years, travel abroad have become a popular activity for tourists and backpacking is among the most popular ways to do it. However, in the case of bad weather or flight delays, how should one choose an alternative flight? This research aims to find the answer to this problem under minimizing time and minimizing cost for choosing an alternative flight for a given travel destination. The research used genetic algorithms to develop a solving algorithm that are based on the evolution of parthenogenesis. In addition, for combinatorial optimization of flights between two countries in Asia, Plato’s genetic algorithm for multi-objective optimization was used to determine the Pareto-optimal front solution set. The results show that the optimized setting of parameters for the algorithm developed by this research are 50 for the population size, 800 for the generation size, and 0.2 for the mutation rate. Moreover, in addition to travel route planning, the proposed algorithm can be applied to other fields, such as solving freight forwarder problems or optimizing cargo loading. Our algorithm can balance between efficiency and quality, which are two important factors emphasized in this era and challenges to international traders.

參考文獻


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