Discrete Event Simulation-Based Evaluation of a Single-Lane Synchronized Dual-Traffic Light Intersections

This research involved an exploratory evaluation of the dynamics of vehicular traffic on a road network across two traffic light-controlled junctions. The study uses the case study of a one-kilometer road system modelled on Anylogic version 8.8.4. Anylogic is a multi-paradigm simulation tool that supports three main simulation methodologies: discrete event simulation, agent-based modeling, and system dynamics modeling. The system is used to evaluate the implication of stochastic time-based vehicle variables on the general efficiency of road use. Road use efficiency as reflected in this model is based on the percentage of entry vehicles to exit the model within a one-hour simulation period. The study deduced that for the model under review, an increase in entry point time delay has a domineering influence on the efficiency of road use far beyond any other consideration. This study therefore presents a novel approach that leverages Discrete Events Simulation to facilitate efficient road management with a focus on optimum road use efficiency. The study also determined that the inclusion of appropriate random parameters to reflect road use activities at critical event points in a simulation can help in the effective representation of authentic traffic models. The Anylogic simulation software leverages the Classic DEVS and Parallel DEVS formalisms to achieve these objectives.

Demand and Capacity Modelling in Healthcare Using Discrete Event Simulation

The NHS is right now confronting huge pressures relating to demand and capacity in radiology. The purpose of this research has been to provide information about MRI usage, details of operational aspects of MRI services, and to ascertain the planning intentions of NHS radiology services to keep up and create MRI capacity. The report expands on using Discrete Event Simulation (DES) to inspect and plan the utilisation of NHS hospital resources for the radiology department to help a 24 hr service that is available to outpatients which will help with diminishing patient waiting time, better resource usage, understanding the capacity and demand. Consequently, this research examines to adjust staff and resources with the demand of the MRI. The research was investigated using DES in various scenarios to find which resources are inactive;patients are treated slowly. DES helped in discovering resource utilisation and outpatient throughout the system. It additionally helped in distinguishing the bottlenecks in patient flow. The DES simulation results demonstrated that time for the outpatient in the system is less and more outpatients have been treated too. There is a higher level of outpatient patients leaving the system under 120 minutes. The report uncovered an MRI report interpretation time. Reception room time and MRI waiting room time are decreased significantly. It additionally exhibited with an expanded outflow of outpatients, resources, for example, MRI capacity and radiographer utilisation expanded.

Discrete Event Simulation to Evaluate Different Treatments of Diabetic Retinopathy Disease

Modeling approach using discrete event simulation has been proven to work well in modeling in health care. The aim of our paper is to propose a simulation approach which shows realistic models presenting different possible treatments in different stages of diabetic retinopathy. We have presented three models in order to choose the best treatment for diabetic retinopathy patients. The first model describes the flow of a patient through stages without any medical treatments. It takes 13 years to reach blindness. The second model which includes the laser photocoagulation treatments leads to blindness after 46 years. Then, the third model illustrates the involvement of vitrectomy operation and delays blindness by 23 years. To construct the models, data were taken from experienced doctors and professors of the ophthalmology department in the University hospital Habib Bourguiba and the endocrinology department in the University hospital Hedi Chaker in Sfax, Tunisia. Our objective is to delay reaching the blindness stage as late as possible. Three models were developed, verified and validated through many iterative implementations with ARENA simulation software.

Parallel architecture and optimization for discrete-event simulation of spike neural networks

Spike neural networks are inspired by animal brains,and outperform traditional neural networks on complicated tasks.However,spike neural networks are usually used on a large scale,and they cannot be computed on commercial,off-the-shelf computers.A parallel architecture is proposed and developed for discrete-event simulations of spike neural networks.Furthermore,mechanisms for both parallelism degree estimation and dynamic load balance are emphasized with theoretical and computational analysis.Simulation results show the effectiveness of the proposed parallelized spike neural network system and its corresponding support components.

Performance-driven design with the support of digital tools： Applying.discrete event simulation and space syntax on the design of the emergency department

Ptanning the design of the emergency department （ED） is a complex process. Hospital readers and architects must consider many complex and interdependent factors, including evolving market demands, patient volume, care models, operational processes, staffing, and medical equipment. The application of digital toots, such as discrete event simulation （DES） and space syntax analysis （SSA）, arrows hospital administrators and designers to quantitativety and objectively optimize their facilities. This paper presents a case study that utitized both DES and SSA to optimize the care process and to design the space in an ED environment. DES was apptied in three phases： master planning, process improvement in the existing ED, and designing the new ED. SSA was used to compare the new design with the existing layout to evatuate the effectiveness of the new design in supporting visuat surveiltance and care coordination. This case study demonstrates that DES and SSA are effective toots for facilitating decision-making retated to design, reducing capital and operational costs, and improving organizational performance. DES focuses on operational processes and care flow. SSA complements DES with its strength in linking space to human behavior. Combining both tools can lead to high-performance ED design and can extend to broad applications in health care.

A discrete event simulation model for waiting time management in an emergency department:A case study in an Egyptian hospital

This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,Egypt.We construct a patient flow division model by dividing patients according to their severity level.Although patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay(LoS),there is a lack in a detailed system evaluation and implementation under this configuration.Based on system observation and health care provider’s interviews,a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system.A discrete event simulation model of the Emergency Department is built using collected data.Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division,including different staff capacities and different patient magnitudes.Results indicate that waiting times and length of patient stay can be significantly improved under the proposed7 system configuration.

Automation of input data to discrete event simulation for manufacturing: A review

Discrete event simulation(DES)is a well-established decision support tool in modeling work flows in manufacturing industry.But,there are an amount of practical and financial obstacles that deter the employment of this technology in industry.One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model.Another issue is the cost of integrating simulation applications with other manufacturing applications.These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing.This review presents the existing research studies in the literature that address the above issues,demonstrating in parallel the already implemented concepts.The scope of this review is to provide an overview of the input data phase,focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.

A Discrete Event Simulation Support System in C^(++)

This paper describes a discrete simulation support system that forms major parts of most simulation program. The support system contains three main features which differ from the most of other simulation support systems. It follows a strict three phase structure; supports visual interactive simulation. The principles of designing and implementing of the system are explained module by module.

Simulation-based Manufacturing System Modeling

In recent years, computer simulation appears to be very advantageous technique for researching the resource-constrained manufacturing system. This paper presents an object-oriented simulation modeling method, which combines the merits of traditional methods such as IDEF0 and Petri Net. In this paper, a four-layer-one-angel hierarchical modeling framework based on OOP is defined. And the modeling description of these layers is expounded, such as: hybrid production control modeling and human resource dispatch modeling. To validate the modeling method, a case study of an auto-product line in a motor manufacturing company has been carried out.

UltraStar:A Lightweight Simulator of Ultra-Dense LEO Satellite Constellation Networking for 6G

The mega-constellation network has gained significant attention recently due to its great potential in providing ubiquitous and high-capacity connectivity in sixth-generation(6G)wireless communication systems.However,the high dynamics of network topology and large scale of mega-constellation pose new challenges to the constellation simulation and performance evaluation.In this paper,we introduce UltraStar,a lightweight network simulator,which aims to facilitate the complicated simulation for the emerging mega-constellation of unprecedented scale.Particularly,a systematic and extensible architecture is proposed,where the joint requirement for network simulation,quantitative evaluation,data statistics and visualization is fully considered.For characterizing the network,we make lightweight abstractions of physical entities and models,which contain basic representatives of networking nodes,structures and protocol stacks.Then,to consider the high dynamics of Walker constellations,we give a two-stage topology maintenance method for constellation initialization and orbit prediction.Further,based on the discrete event simulation(DES)theory,a new set of discrete events is specifically designed for basic network processes,so as to maintain network state changes over time.Finally,taking the first-generation Starlink of 11927 low earth orbit(LEO)satellites as an example,we use UltraStar to fully evaluate its network performance for different deployment stages,such as characteristics of constellation topology,performance of end-to-end service and effects of network-wide traffic interaction.The simulation results not only demonstrate its superior performance,but also verify the effectiveness of UltraStar.

Evaluation of the impact of commodity price change on mine plan of underground mining

Fluctuations in commodity prices should influence mining operations to continually update and adjust their mine plans in order to capture additional value under new market conditions. One of the adjustments is the change in production sequencing. This paper seeks to present a method for quantifying the net present value(NPV) that may be directly attributed to the change in commodity prices. The evaluation is conducted across ten copper price scenarios. Discrete event simulation combined with mixed integer programming was used to attain a viable production strategy and to generate optimal mine plans. The analysis indicates that an increase in prices results in an increased in the NPV from$96.57M to $755.65M. In an environment where mining operations must be striving to gain as much value as possible from the rights to exploit a finite resource, it is not appropriate to keep operating under the same mine plan if commodity prices alter during the course of operations.

Digitalization of mine operations:Scenarios to benefit in real-time truck dispatching

One of the key factors in a profitable open-pit mine is the efficiency of the waste disposal system. Using GPS-technology, the truck-dispatching decisions can be made in real-time but the chosen strategy has a crucial role. Therefore, finding the optimal dispatching strategy for truck-shovel operations is extremely important. Dispatching strategies have been reported in the literature, but the comparison of these strategies is still missing. This paper illustrates the differences between the strategies by conducting a stochastic simulation study based on the data gathered from an actual mine. The findings underline the importance of the global vision in dispatching decisions.

Workshop Scheduling Based on a Rule-restrained Colored Petri Net and the Development of a Scheduling System on the Internet/Intranet

In the paper, the gap between theoretical research and practical applicationsof workshop scheduling is analyzed. According to practical application requirements, thetraditional Petri net is expanded and a Rule-restrained Colored Petri Net (RCPN) is put forward tomodel workshop activities. Then, the architecture of the workshop scheduling system based on RCPN ispresented. Finally, the scheduling system that adopts a 3 -layer B/S/D mode is developed on theInternet/Intranet by using the Web database and Java.

Reliability and Feedback of Multiple Hop Wireless Networks

This paper analyzes fault-tolerance over the entire design life of a class of multiple-hop wireless networks, where cooperative transmission schemes are used. The networks are subject to both node failure and random channel fading. A node lifetime distribution is modeled with an increasing failure rate, where the node power consumption level enters the parameters of the distribution. A method for assessing both link and network reliabilities projected at the network＇s design life is developed. Link reliability is enhanced through use of redundant nodes. The number of redundant nodes is restricted by the cooperative transmission scheme used. The link reliability is then used to establish a re-transmission control policy that minimizes an expected cost involving power, bandwidth expenditures, and packet loss. The benefit and cost of feedback in network operations are examined. The results of a simulation study under specific node processing times are presented. The study quantifies the effect of loop closure frequency, acknowledgment deadline, and nodes＇ storage capacity on the performance of the network in terms of network lifetime, packet loss rate, and false alarm rate. The study concludes that in a network where energy is severely constrained, feedback must be applied judiciously.

A Model Combining Discrete Event System Simulation and Genetic Algorithm for Buffer Allocation in Unreliable Large Production Lines

To solve the difficulties in allocating buffers for unreliable large production lines, this paper inves-tigated a model combining the genetic algorithm with the discrete event system simulation method. In the simulation method, times-to-failure of an unreliable large production line is assumed to follow exponential distribution, whereas times-to-repair and times-to-processing are set to follow an Erlang-k distribution. Using a genetic algorithm based on special position-based mapping means and elitist protection strategy, the buffer configuration of an auto-body welding line is optimized. The simulation of the optimized configuration shows that the performance of the production line, such as productivity and the main average utilization of the workstations, is much improved. This model can optimize the allocation of buffers for unreliable large production lines effectively.

An Intelligent Agent Approach to Adaptive Project Management

This paper presents the initial steps to integrating a distributed discrete event simulation system with a framework for intelligent software agents. The resulting system has a simulation component that is based on the high-level architecture (HLA) and an agent component that implements the belief-desire-intention (BDI) approach to agent modelling. The architecture is connected to a real-time information source. The framework was successfully applied to a real-life monitoring system for a tunnel-boring machine excavation project that helped with forecasting and managing the project timelines in response to the changes in the uncertain excavation environment. This project is presented as a test case and demonstrates encouraging results for integrative modelling of large-scale problems with elements of uncertainty.

A Multilevel Splitting Algorithm for Quick Sampling

To reduce intermediate levels of splitting process and enhance sampling accuracy, a multilevel splitting algorithm for quick sampling is proposed in this paper. Firstly, the selected area of the elite set is expanded to maintain the diversity of the samples. Secondly, the combined use of an adaptive difference evolution algorithm and a local searching algorithm is proposed for the splitting procedure. Finally, a suite of benchmark functions are used for performance testing. The results indicate that the convergence rate and stability of this algorithm are superior to those of the classical importance splitting algorithm and an adaptive multilevel splitting algorithm.

A multi-level splitting algorithm based on differential evolution

Multi-level splitting algorithm is a famous rare event simulation(RES)method which reaches rare set through splitting samples during simulation.Since choosing sample paths is a key factor of the method,this paper embeds differential evolution in multi-level splitting mechanism to improve the sampling strategy and precision,so as to improve the algorithm efficiency.Examples of rare event probability estimation demonstrate that the new proposed algorithm performs well in convergence rate and precision for a set of benchmark cases.

Formal verification with HiLLS-specified models:A further step in multi-analysis modeling of complex systems

The multi-analysis modeling of a complex system is the act of building a family of models which allows to cover a large spectrum of analysis methods(such as simulation,formal methods,enactment,...)that can be performed to derive various properties of this system.The High-Level Language for Systems Specification(HiLLS)has recently been introduced as a graphical language for discrete event simulation,with potential for other types of analysis,like enactment for rapid system prototyping.HiLLS defines an automata language that also opens the way to formal verification.This paper provides the building blocks for such a feature.That way,a unique model can be used not only to perform both simulation and enactment experiments but also to allow the logical analysis of properties without running any experiment.Therefore,it saves from the effort of building three different analysis-specific models and the need to align them semantically.

An early discharge approach for managing hospital capacity

The Kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited capacity.Arrival patients who find all beds occupied are simply turned away,i.e.,no waiting is allowed.This paper investigates the impact of an early discharge approach that can be applied to patients that have been scheduled to discharge within 5 h.A discrete event simulation(DES)model is built using empirical distributions based on real data.The model has been validated against real data and the results have shown that the proposed early discharge approach can reduce the number of turned away patients by 10%in the Kidney Department,equivalent to 182 patients annually and by 11%in the Oncology Department,equivalent to 150 patients annually.