The tourism industry admitted by World Tourism Organization is one of the greatest growth industry. In Japan, this industry has big influence for economics, employments and regional activations. In 2003, Japanese government regarded own country as tourism country and has been doing various policies to makes Japan tourism country. According to the statistical data from home page of Japan Tourism Agency, the number of foreign tourists visiting Japan reached 24.04 million in 2016, marking a 21.8% increase over the previous record of 19.74 million set in 2015 and setting a new record high for a fourth consecutive year. Against this backdrop, the national average guest room occupancy rate of lodging facilities in Japan was 60.0% in 2016. However, it is noteworthy that a major disparity in guest room occupancy rates has occurred between urban areas and regional areas. The guest room occupancy rates in Tokyo and Osaka Prefecture were 79.4% and 84.1%, respectively, whereas in ten prefectures, they were below 50%, with Nagano Prefecture having the lowest rate: 35.5%. In these circumstances, regional tourism promotion is essential for implementing the Japanese government's regional revitalization policies. Accordingly, in the present study, for the purpose of considering the increase of guest room occupancy rates of the lodging facilities in regional areas, we performed analysis of the popularity of hotel plans in Yamanashi Prefecture, which is located near Tokyo, and in Okinawa Prefecture, where the number of tourists from overseas has increased in recent years. To ascertain hotel plan options, we used morphological analysis of plan names. And We created plan groups by cluster analysis. We defined the purchase rate as an indicator for measuring hotel plan popularity. For the purpose of ascertaining hotel plan popularity, we use multiple regression analysis. As a result, we obtained new knowledge about hotel plan popularity.

Tourism is recognized by the United Nations World Tourism Organization as the worlds' largest growth industry. Tourism in Japan has a tremendous impact on the Japanese economy, including employment and regional vitalization. The Japanese government designated Japan as a “tourism-oriented country” in 2003 and has implemented various tourism promotion measures. In the present research, we attempted to ascertain hotel plan purchasing factors by devising “purchase rate” as an indicator that expresses sales of hotel plans in each region by using daily data on the number of room vacancies and number of full occupancy days for hotel plans of hotels in each region, focusing analysis on hotels in Kyoto, a global travel destination, as well as those in Osaka and Kobe, major areas in the Kinki region. In our analysis, we used k-means, a non-hierarchical cluster analysis method, in hotel plan grouping. We discovered seasonal fluctuations and a day-of-the-week effect in hotel plan sales in each area and obtained new knowledge concerning hotel plan popularity factors by excluding the day-of-the-week effect.

To enable efficient transportation in semiconductor fabrication bays, it is necessary to generate route planning of multiple automated guided vehicles (AGVs) efficiently to minimize the total transportation time without collision among AGVs. In this paper, we propose a distributed route-planning method for multiple mobile robots using an augmented Lagrangian decomposition and coordination technique. The proposed method features a characteristic that each AGV individually creates a near-optimal routing plan through repetitive data exchange among the AGVs and local optimization for each AGV. Dijkstra's algorithm is used for local optimization. The optimality of the solution generated by the proposed method is evaluated by comparing the solution with an optimal solution derived by solving integer linear programming problems. A near-optimal solution, within 3% of the average gap from the optimal solution for an example transportation system consisting of 143 nodes and 14 AGVs, can be derived in less than 5 s of computation time for 100 types of requests. The proposed method is implemented in an experimental system with three AGVs, and the routing plan is derived in the configuration space, taking the motion of the robot into account. It is experimentally demonstrated that the proposed method is effective for various problems, despite the fact that each route for an AGV is created without minimizing the entire objective function.

For the transportation in semiconductor fabricating bay, route planning of multiple AGVs (Automated Guided Vehicles) is expected to minimize the total transportation time without collision and deadlock among AGVs. In this paper, we propose a distributed route planning method for multiple mobile robots using Lagrangian decomposition technique. The proposed method has a characteristic that each mobile robot individually creates a near optimal route through the repetitive data exchange among the AGVs and the local optimization of its route using Dijkstra's algorithm. The proposed method is successively applied to transportation route planning problem in semiconductor fabricating bay. The optimality of the solution generated by the proposed method is evaluated by using the duality gap derived by using Lagrangian relaxation method. A near optimal solution within 5% of duality gap for a large scale transportation system consisting of 143 nodes and 15 AGVs can be obtained only within five seconds of computation time. The proposed method is implemented on 3 AGVs system and the route plan is derived taking the size of AGV into account. It is experimentally shown that the proposed method can be found to be effective for various types of problems despite the fact that each route for AGV is created without considering the entire objective function.