Simulation-based Evaluation of Urban Consolidation Centers Considering Urban Access Regulations

The negative effects of urban freight transports, such as air quality problems, road congestion, and noise emissions lead in many cities to major difficulties. A widely studied measure to reduce these negative effects are Urban Consolidation Centers (UCCs), which aim to bundle freight flows to reduce the number of urban freight transports. However, many projects showed that the additional costs of UCCs often made it unattractive for carriers to participate in such schemes. This paper presents an agent-based simulation to assess the impact of urban access regulations on the cost-attractiveness of UCCs for carriers. A case study inspired by the Frankfurt Rhine-Main area is presented to compare deliveries of a group of carriers with and without a Urban Consolidation Center under various urban access scenarios. The simulation shows that regulations increase the cost-attractiveness of UCCs for carriers to varying degrees while increasing the overall traffic volume.

A Simulation Model to Assess the Impact of Insurance Expansion on Colorectal Cancer Screening at the Population Level

Recent US healthcare reform debates have triggered substantial discussion on how best to improve access to insurance. Colorectal cancer (CRC) is an example of a largely preventable condition, if access to and use of healthcare is increased. Early and ongoing screening and intervention can identify and remove polyps before they become cancerous. We present the development of an individual-based discrete-event simulation model to estimate the impact of insurance expansion scenarios on CRC screening, incidence, mortality, and costs. A national repeated cross-sectional survey was used to estimate which individuals obtained insurance in North Carolina (NC) after the Affordable Care Act (ACA). The potential impact of expanding the state’s Medicaid program is tested and compared to no insurance reform and the ACA without Medicaid expansion. The model integrates a census-based synthetic population, national data, claims based statistical models, and a natural history module in which simulated polyps and cancer progress.

Building a Flexible Simulation Model for Modeling Multiple Outpatient Orthopedic Clinics

This study is designed to demonstrate the benefit of using a single simulation model in order to analyze operations at two distinct, but related, pediatric orthopedic outpatient clinics in Massachusetts. A simulation model with a built-in dashboard is constructed for the clinics using AnyLogic. The constructed simulation model has been proven to be a useful tool in anticipating the effects of changes in system features such as patient volume, provider team mix, and exam room assignment policies. With the development of a flexible simulation model the ultimate goal is to assist clinic managers in their efforts to reduce patient waiting time and lengths of stay in the two distinct orthopedic clinics.

A Simulation and Online Optimization Approach for the Real-time Management of Ambulances

Emergency Medical Service (EMS) is one of the most important health care services as it plays a vital role in saving people’s lives and reducing the rate of mortality and co-morbidity. The importance and sensitivity of decision making in the EMS field have been recognized by researchers who studied many problems arising in the management of EMS systems since the 1960. Some authors of similar research present a review of the many simulation models that have been developed over the years: most of the available simulation approaches are based on a Discrete Event Simulation (DES) approach.

Improving Quality of Care in a Multidisciplinary Emergency Department by the Use of Simulation Optimization: Preliminary Results

Emergency department (ED) crowding is a worldwide challenge. It adversely affects quality of care, patient safety, and employee satisfaction. The magnitude of ED crowding can be measured by the quality metrics length-of-stay (LOS), the patient’s door-to-doctor-time (DTD), and the 4-hourstandard. This standard states that 95% of the patients stay less than four hours within the ED. In order to improve those metrics, healthcare processes have to be welldesigned and resource capacity has to match the ever increasing demand. We implemented a validated, detailed discrete-event simulation model of a multidisciplinary ED in Germany to provide decision support for ED managers. Our model incorporates several patient flows considering patients and resources of two different medical specialties. The introduced simulation model was parameterized according to real-world data. Leveraging OptQuest and AnyLogic, we combined optimization and simulation to find input staffing levels that minimize the avg. LOS of patients. Simulation experiments show that certain process modifications, nurse pooling, and optimized staffing levels lead to improvements in quality of care. With respect to that, both avoiding boarding of inpatients and implementing nurse pooling result in a decrease of more than 14% in avg. LOS and are particularly promising. We also identified that reallocating capacities from internists to nurses dedicated to internal medicine patients enhances the quality of care.

Capacity Analysis for Aircrew Training Schools - Estimating Optimal Manpower Flows Under Time Varying Policy and Resource Constraints

Capacity analysis for systems with time varying constraints is still an open problem in Operations Research due to the non-stationarity of the problem domain. This is particularly true for Defence manpower supply which is subject to frequent temporal policy and resource changes. As such, the problem cannot be completely covered with a single overriding simulation or optimisation solution, but, rather, better described using piecewise interplay between simulation and optimisation. This paper describes such an approach for a flexible, interactive capacity analysis simulator with an embedded integer linear programming (ILP) optimiser.

Multi-fidelity Simulation Optimisation for Airline Disruption Management

The airline industry faces many causes of disruption. To minimise financial and reputational impact, the airline must adapt its schedules. Due to the complexity of the environment, simulation is a natural modelling approach. However, the large solution space, time constraints and system constraints make the search for revised schedules difficult. This paper presents a method for the aircraft recovery problem that uses multi-fidelity modelling including a trust region simulation optimisation algorithm to mitigate the computational costs of using high-fidelity simulations with its benefits for providing good estimates of the true performance.

A Comprehensive Electricity Market Model Using Simulation And Optimization Techniques

Worldwide Electrical Power Systems (EPSs) are faced with tremendous challenges because of the reduction of greenhouse gas emissions and the increasing number of renewables. EPS analysis can help to show future developments in an uncertain environment and is an important task for the assessment of greenhouse gas emissions. In order to perform such a complex analysis of future EPSs, a huge number of input parameters is needed. Moreover, technical and also economical processes have to be considered. Thereby, one major task is the modeling of electricity markets. In this paper, we present an approach for the modeling of the German EPS including electricity markets using hybrid simulation and mathematical optimization. We contribute an object-oriented electricity market model which can be utilized to study different exchange mechanisms and behavior patterns of generation unit operators. Simulation results show market results for different generation unit operators and realistic market prices.

Simulation-based Headway Optimization for a Subway Network: a Performance Comparison of Population-based Algorithms

This study presents simulation-based optimization for the Viennese subway system. The underlying discrete event simulation model has several stochastic elements like time-dependent demand and turning maneuver times, direction-dependent vehicle travel and passenger travel as well as transfer times. Passenger creation is a Poisson process which uses hourly origin-destination-matrices based on mobile phone data. The number of waiting passengers on platforms and within vehicles are subject to capacity restrictions. As a microscopic element, passenger distribution along platforms and within vehicles is considered. There are trade-offs between service quality (e.g. waiting time) and costs (e.g. fleet mileage). This bi-objective optimization problem is transformed into a single-objective one by normalization and scalarization. The goal is to find optimal time-dependent headways. Computational experience is gained from 48 test instances which are based on real-world data. Several population-based evolutionary algorithms were applied. The covariance matrix adaptation evolution strategy (CMA-ES) performed best.

Hybrid Simulation Challenges and Opportunities: a Life-cycle Approach

The last 10 years have witnessed a marked upsurge of attention on Hybrid Simulation (HS). The majority of authors define HS as a joint modelling approach which includes two or more simulation approaches (mainly Discrete Event Simulation, System Dynamics and Agent Based Simulation). Whilst some may argue that HS has been in existence for more than 5 decades, the recent rise tended to be more problem driven rather than technical experimentation. Winter Simulation Conference (WSC) 2015, 2016, 2017 have witnessed 3 panels on the purpose, history and definition of HS, respectively. This paper reports on a comprehensive review conducted by the panelists on HS and its applications.