Spherical bipolar fuzzy weighted multi-facility location modeling for mobile COVID-19 vaccination clinics

A pandemic was declared in 2020 due to COVID-19. The most important way to deal with the virus is mass vaccination which is a complex task in terms of fast transportation and process management. Hospitals and other health centers can be used for vaccination. In addition, in order to separate other diseases from COVID-19 and provide rapid access to vaccines, mobile vaccination clinics can also be considered. In this study, the location assignments of mobile vaccination clinics that can serve some regions of three cities in Turkey are examined. The linear formulation of the problem is given, and the multi-facility location problem for COVID-19 vaccination is investigated with Lagrange relaxation and modified saving heuristic algorithm. For the proposed fuzzy MCDM integrated saving heuristic, the importance of candidate locations is calculated with the aid of decision makers who give their views in spherical bipolar fuzzy information. The results of different approaches are compared, and it is intended to guide future studies.

Change of Scene: The Geographic Dynamics of Resilience to Vehicular Accidents

Most have experienced the impact of vehicular accidents, whether it was in terms of increased commute time, delays in receiving goods, higher insurance premiums, elevated costs of services, or simply absorbing the daily tragedies on the evening news. While accidents are common, the complexity and dynamics of transportation systems can make it challenging to infer where and when incidents may occur, a critical component in planning for where to position resources for emergency response. The use of response resources is critical given that more efficient emergency responses to accidents can decrease the vulnerability of socio-economic systems to perturbations in the transportation system and contribute to greater resilience. To explore the resilience of transportation systems to disruptions due to vehicular accidents, a location modeling approach is described for identifying the origins of optimal responses (and associated response time) over time based upon the location of known accidents and response protocols. The characteristics of the modeled response can then be compared with those of the observed response to gain insights as to how resilience may change over time for different portions of the transportation system. The change in the location of the optimal sites over time or drift, can also be assessed to better understand how changes in the spatial distribution of accidents can affect the nature of the response and system resiliency. The developed approach is applied to investigate the dynamics of accident response and network resiliency over a three year period using vehicular crash information from a comprehensive statewide database.

Location Modeling of Final Palaeolithic Sites in Northern Germany

Location modeling, both inductive and deductive, is widely used in archaeology to predict or investigate the spatial distribution of sites. The commonality among these approaches is their consideration of only spatial effects of the first order (i.e., the interaction of the locations with the site characteristics). Second-order effects (i.e., the interaction of locations with each other) are rarely considered. We introduce a deductive approach to investigating such second-order effects using linguistic hypotheses about settling behavior in the Final Palaeolithic. A Poisson process was used to simulate a point distribution using expert knowledge of two distinct hunter–gatherer groups, namely, reindeer hunters and elk hunters. The modeled points and point densities were compared with the actual finds. The G-, F-, and K-function, which allow for the identification of second-order effects of varying intensity for different periods, were applied. The results reveal differences between the two investigated groups, with the reindeer hunters showing location-related interaction patterns, indicating a spatial memory of the preferred locations over an extended period of time. Overall, this paper shows that second-order effects occur in the geographical modeling of archaeological finds and should be taken into account by using approaches such as the one presented in this paper.