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The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee., Poster Session P39

In Japan in recent years, policies for compact cities have been promoted as the population has decreased, and the use of micro-geo data has attracted attention in urban planning. Therefore, when considering a compact city, it is important to know the relationship between the urban facility layout and the population flow. In this research, we created a data set using demographic data, location information of mobile phones, and detailed building data and used a radial basis function (RBF) network. In short, the purpose of this study was to develop a method to reduce the estimated area of population inflow per hour. Population inflow is expressed as the visiting population, which is defined by the difference in the staying population in the time of two sections. By spatially visualizing the results, we were able to downscale the population flow data on a 500 m grid.

In Japan in recent years, policies for compact cities have been promoted as the population has decreased, and the use of micro-geo data has attracted attention in urban planning. Therefore, when considering a compact city, it is important to know the relationship between the urban facility layout and the population flow. In this research, we created a data set using demographic data, location information of mobile phones, and detailed building data and used a radial basis function (RBF) network. In short, the purpose of this study was to develop a method to reduce the estimated area of population inflow per hour. Population inflow is expressed as the visiting population, which is defined by the difference in the staying population in the time of two sections. By spatially visualizing the results, we were able to downscale the population flow data on a 500 m grid.

The rise of radiofrequency scanner technology has led to its potential application in the observation of people’s movements. This study used aWi-Fi scanner device to track tourists’ traveling behavior inHokkaido’s tourismarea,whichoccupies a large regionthat features auniquenatural landscape. Inbound tourists have significantly increased in recent years; thus, tourism’s sustainability is considered to be important formaintaining the tourismatmosphere in the long term. Using internet-enabled technology to conduct extensive area surveys can overcome the limitations imposed by conventional methods. This study aims to use digital footprint data to describe and understand traveler mobility in a large tourism area in Hokkaido. Association rule mining (ARM)—a machine learning methodology—was performed on a large dataset of transactions to identify the rules that link destinations visited by tourists. This process resulted in the discovery of traveling patterns that revealed the association rules between destinations, and the attractiveness of the destinations was scored on the basis of visiting frequency, with both inbound and outbound movements considered. A visualization method was used to illustrate the relationships between destinations and simplify the mathematical descriptions of traveler mobility in an attractive tourism area. Hence, mining the attractiveness of destinations in a large tourism area using an ARMmethod integrated with aWi-Fi mobility tracking approach can provide accurate information that forms a basis for developing sustainable destination management and tourism policies.

Evacuation planning and shelter site selection are the most important function of disaster management for the purpose of helping at-risk persons to avoid or recover from the effect of a disaster. This study aims to propose a stochastic linear mixed-integer mathematical programming model for improving flood evacuation planning and shelter site selection under a hierarchical evacuation concept. The hierarchical evacuation concept is applied in this study that balances the preparedness and risk despite the uncertainties of flood events. This study considers the distribution of shelter sites and communities, evacuee's behavior, utilization of shelter and capacity restrictions of the shelter by minimizing total population-weighted travel distance. We conduct computational experiments to illustrate how the proposed methodical model works on a real case problem in which we proposed Thai flooding case study. Also, we perform a sensitivity analysis on the parameters of the mentioned mathematical model and discuss our finding. This study will be a great significance in helping policymakers consider the spatial aspect of the strategic placement of flood shelters and evacuation planning under uncertainties of flood scenarios.

Since the 1950s, the number of natural and man-made disasters has increased exponentially and the facility location problem has become the preferred approach for dealing with emergency humanitarian logistical problems. To deal with this challenge, an exact algorithm and a heuristic algorithm have been combined as the main approach to solving this problem. Owing to the importance that an exact algorithm holds with regard to enhancing emergency humanitarian logistical facility location problems, this paper aims to conduct a survey on the facility location problems that are related to emergency humanitarian logistics based on both data modeling types and problem types and to examine the pre- and post-disaster situations with respect to facility location, such as the location of distribution centers, warehouses, shelters, debris removal sites and medical centers. The survey will examine the four main problems highlighted in the literature review: deterministic facility location problems, dynamic facility location problems, stochastic facility location problems, and robust facility location problems. For each problem, facility location type, data modeling type, disaster type, decisions, objectives, constraints, and solution methods will be evaluated and real-world applications and case studies will then be presented. Finally, research gaps will be identified and be addressed in further research studies to develop more effective disaster relief operations.