Towards the Holy Grail: combining system dynamics and discrete-event simulation in healthcare

The idea of combining discrete-event simulation and system dynamics has been a topic of debate in theoperations research community for over a decade. Many authors have considered the potential benefits ofsuch an approach from a methodological or practical standpoint. However, despite numerous examples ofmodels with both discrete and continuous parameters in the computer science and engineering literature,nobody in the OR field has yet succeeded in developing a genuinely hybrid approach which truly integratesthe philosophical approach and technical merits of both DES and SD in a single model. In this paperwe consider some of the reasons for this and describe two practical healthcare examples of combinedDES/SD models, which nevertheless fall short of the “holy grail” which has been so widely discussed inthe literature over the past decade

Cost-based filtering for stochastic inventory control

Abstract. An interesting class of production/inventory control problems considers a single product and a single stocking location, given a stochastic demand with a known non-stationary probability distribution. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using a cost-based filtering method. Our algorithm can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all.

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 2: The Physics Program for DUNE at LBNF

The Physics Program for the Deep Underground Neutrino Experiment (DUNE) at the Fermilab Long-Baseline Neutrino Facility (LBNF) is described

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

A comparison of discrete event simulation and system dynamics for modelling health care systems

In this paper we discuss two different approaches to simulation, discrete event simulation and system dynamics. Both have been used widely in the health care domain, although there are fewer applications of system dynamics. The aim of this paper is not to give a comprehensive survey of the literature, but rather to discuss whether the choice of methodology is purely the personal preference of the modeller, or whether there are identifiable features of certain systems that make one methodology superior to the other. We illustrate the use of these techniques by considering two case studies, a simple discrete event simulation model of HIV/AIDS and a system dynamics model of the UK cardiac surgery system. We attempt to draw up some guidelines to assist the modeller in making the choice of technique

Modeling human behavior: an (id)entity crisis?

Agent-based modeling (ABM) has gained great popularity in recent years, especially in application areas where human behavior is important, because it opens up the possibility of capturing such behavior in great detail. Hybrid models which combine ABM with discrete-event simulation (DES) are particularly appealing in service industry applications. However in this paper we argue that many of the so-called distinctions between agents in an ABM and entities in a DES are artificial, and we describe several DES models which use standard entities to represent agent-like behaviors

Modelling for HIV infection and AIDS

SIGLEAvailable from British Library Document Supply Centre- DSC:DX178953 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Tutorial: Advances and challenges in healthcare simulation modeling

Simulation has been used for modeling healthcare systems for over forty years. In many respects it is the ideal approach for addressing healthcare issues, yet the relatively small number of successful implementations would suggest that (outside academia) it has been underused in the health sector, compared with manufacturing industry or defense. In this paper we present a review of applications of simulation in healthcare, focusing on successful implementations, and we discuss some possible reasons why simulation has arguably failed to fulfill its potential. We describe recent advances in the area and identify opportunities for further research and new developments