摘要
由於經濟的發展使得人們越來越重視旅遊休閒活動，但由於時間與金錢之限制，大部份國人還是以短途的旅遊為主，旅遊者往往會在某個縣市或區域作深入之遊玩。這使得短途的旅遊行程規劃具有相當高的實用性。一個好的旅程規劃不僅要能同時滿足旅遊者對時間、金錢與喜好等多種不同條件之限制，更要讓旅遊者在旅遊過程中得到最大之樂趣。所以旅程規劃並不是一件容易的工作，因為要從眾多的旅遊景點中，選出適合之景點建構出一條符合多種不同需求之最佳旅遊路線，是一個很困難的多重限制最佳化問題。因此本論文提出一套旅遊路線規劃支援系統，以台南市的旅遊景點為對象，利用基因與蟻群演算法，根據旅遊者所輸入的時間與金錢預算，以及個人喜歡之旅遊主題與景點，規劃出可獲得最大樂趣的旅遊路線。為驗證所提方法之效能，在本論文中以一系列不同大小之網路進行實驗，並比較基因與蟻群演算法的優劣。
並列摘要
With the growing of national economy and the deployment of two-day weekend policy, people in Taiwan pay more attention to leisure tours. Most people plan their traveling routes without the help of travel agents. However, planning a tour is a very complicated task because it must consider many requirements such as travel time, budget and preference. Generally speaking, a route planning problem can be viewed as a multi-constrained optimization problem. Such a problem cannot be solved with a polynomial-time algorithm. This study applies Genetic Algorithm and Ant Colony Optimization to solve the multi-constrained route planning problem. Experiments results show that the proposed algorithms are effective. Moreover, to alleviate the load of planning traveling route, this study utilizes the proposed algorithms and the WEB technologies to constructs a travel route planning support system.