Fast flow algorithm prioritizing the most time-consuming source point by using a multi-source evacuation model

In many public spaces (e.g. colleges and shopping malls), people are frequently distributed discretely, and thus, single-source evacuation, which means there’s only one point of origin, is not always a feasible solution. Hence, this paper discusses a multi-source evacuation model and algorithm, which are intended to evacuate all the people that are trapped within the minimum possible time. This study presents a fast flow algorithm to prioritize the most time-consuming source point under the constraint of route and exit capacity to reduce the evacuation time. This fast flow algorithm overcomes the deficiencies in the existing global optimization fast flow algorithm and capacity constrained route planner (CCRP) algorithm. For the fast flow algorithm, the first step is to determine the optimal solution to single-source evacuation and use the evacuation time of the most time-consuming source and exit gate set as the initial solution. The second step is to determine a multi-source evacuation solution by updating the lower limit of the current evacuation time and the exit gate set continually. The final step is to verify the effectiveness and feasibility of the algorithm through comparison.

Numerical convergence of pre-initial conditions on dark matter halo properties

ABSTRACT Generating pre-initial conditions (or particle loads) is the very first step to set up a cosmological N-body simulation. In this work, we revisit the numerical convergence of pre-initial conditions on dark matter halo properties using a set of simulations which only differs in initial particle loads, i.e. grid, glass, and the newly introduced capacity constrained Voronoi tessellation (CCVT). We find that the median halo properties agree fairly well (i.e. within a convergence level of a few per cent) among simulations running from different initial loads. We also notice that for some individual haloes cross-matched among different simulations, the relative difference of their properties sometimes can be several tens of per cent. By looking at the evolution history of these poorly converged haloes, we find that they are usually merging haloes or haloes have experienced recent merger events, and their merging processes in different simulations are out-of-sync, making the convergence of halo properties become poor temporarily. We show that, comparing to the simulation starting with an anisotropic grid load, the simulation with an isotropic CCVT load converges slightly better to the simulation with a glass load, which is also isotropic. Among simulations with different pre-initial conditions, haloes in higher density environments tend to have their properties converged slightly better. Our results confirm that CCVT loads behave as well as the widely used grid and glass loads at small scales, and for the first time we quantify the convergence of two independent isotropic particle loads (i.e. glass and CCVT) on halo properties.

Capacity Rationing in Primary Care: Provider Availability Shocks and Channel Diversion

We study capacity rationing by servers facing differentiated customer classes using data from the Veterans Health Administration, which is the largest integrated healthcare system in the U.S. Using more than 11 million health encounters over two years in which the system was capacity constrained, our study provides a comprehensive analysis of the impacts of provider availability shocks on care channel diversion and delays. The outcomes studied include emergency room (ER) visits broken down by type, urgent care center visits, office and phone visits with one’s own versus another provider, post-ER follow-up visits, and ER readmissions. Availability shocks in our analysis are a residualized measure characterizing weeks in which the provider has fewer (or more) office appointments than expected based on typical patterns. The main finding is that moving from two standard deviations above to two standard deviations below in availability shocks increases ER visits by 2.4%, or about 20,000 yearly ER visits. Interestingly, the increase in ER visits is only present for the non-emergent category, indicating differentiated service to emergent and non-emergent care requests; capacity-constrained providers still tend to the patients in most need. Another finding is that provider availability shocks delay and divert post-ER follow-up care. Yet there is no effect on ER readmissions, a severe outcome of delayed or foregone follow-up, indicating that providers ration by priority these follow-up appointments. This paper was accepted by Vishal Gaur, operations management.