Our approach includes four components: create a game/story narrative; discuss, evaluate, and expand the narrative; implement the narrative into an animated storyboard; and implement the narrative into a simulation.

This work presents a mathematical formulation and a solving approach based on a metaheuristic for the resource allocation problem. This approach is designed to deal with data-intensive applications, which must guarantee the availability of the data at all times.

This paper proposes a simheuristic algorithm for solving the stochastic team orienteering problem, where goals other than maximizing the expected reward need to be considered. A series of numerical experiments contribute to illustrate the potential of our approach, which integrates Monte Carlo simulation inside a metaheuristic framework.

In this paper, we present our approach for a utilization target estimation system which bases its estimation on a wide range of data points created by data farming. Then, we apply a regression analysis to interpolate missing data points in order to provide fast estimates for utilization limits depending on equipment characteristics.

Our research employs a parallel discrete event simulation simulator, Neuron Time Warp (NTW), which is intended for use for the simulation of neurons.

This paper focuses on the fillet batching process. To minimize the giveaway of fixed-weight fillet batching the right choices on layout, buffer sizes, batch sizes and batch allocation policies are of great importance.

In this paper a practical case from an Austrian mechanical engineering company is presented. Simulation based manufacturing system improvement is applied to their component manufacturing plant. The results of this simulation study show that service level and inventory can be significantly improved by optimization of planning parameters and reduction of setup times. In addition, the study shows that load-dependent outsourcing is a viable alternative to capacity investment.

This paper presents a hybrid QCSP (Quay Crane Scheduling Problem) Solver, which combines genetic algorithms for global search with steepest ascent hill climbing for local search. Numerical experiments are performed with small- and large-sized random QCSP instances. The experimental results revealed that the hybrid QCSP Solver provides a better solution than the stand-alone QCSP Solver.

In this work, we integrate DEVS and CPLEX, a mathematical programming optimization software, to develop a simulation-optimization scheduling methodology for nuclear medicine clinics.

Most common sawmill log yards are operated by wheel loaders or log stackers. As the operational costs of this form of transportation are quite high, new technologies might be advantageous. This study assesses the feasibility and the requirements for a technology to allow a high degree of automation of the log yard operations using automated storage components. The results of the simulation study enable an educated assessment of the required dimension of the automated log storage for different scenarios.

In this paper, simulation is used to model and experiment on a case with three end products in order to determine the relationship between safety stock levels and service levels. The result is that simulation can provide a much more accurate determination of safety stock levels for intermittent demands than theoretical calculations.

This work presents a simulative approach to combine material flow simulation with the energy flow simulation for a foundry use case.

In this paper, we develop a data informatics model that could be used to realize a digital synchronized supply chain. To realize this model, we take a hybrid approach that combines Bayesian modeling with discrete event simulation and apply it to the supply chain process of a Procter & Gamble manufacturing and distribution facility.

The paper presents first results using our framework and investigates the procedure with regard to the solutions quality and runtime requirements.

Technological and business modelling today is one of the most effective ways of forecasting in management decision making. The paper considers simulation model of vessels queue on a sea port’s roads in a generic way. Concerns of correlations between the mechanism of berth nomination for a vessel on one hand and length and structure of queue of vessels on port’s roads on the other hand are risen. Results of experiments with the developed model are discussed.

This paper describes the Simio modeling system that is designed to simplify model building by promoting a modeling paradigm shift from the process orientation to an object orientation.

In this paper, an approach for modeling, integrating and executing user-generated actions into the decision support system is described, in order to increase its flexibility and usability. In conclusion, the authors propose to develop a domain-specific modeling language for modeling actions for discrete-event simulation models.

This paper presents a new sensor-informed resampling method which utilizes sensor data to improve resampling of particles. Experiment results show the new method was able to provide better estimation of the system state with a limited number of particles compared to the standard bootstrap filter.

This paper discusses the importance, historical significance, and prestige of the Computer Simulation Archive (https://d.lib.ncsu.edu/computer-simulation/) at North Carolina State University Libraries, including its importance to the field of simulation and its place in the broader context of research library archival collections.

We develop a discrete-event simulation of a multi-echelon supply chain, utilizing Rockwell Automation’s Arena software tool, to investigate this phenomenon. We investigate inventory order history blackouts of three different durations (1, 2, and 3 time periods).

The application of the proposed simulation model was demonstrated in a case study of the City of Miami Beach. The simulation results identified the intersectional effects of various factors in household water conservation technology adoption and also investigated the scenario landscape of the adoptions that can inform policy formulation and planning.

In this paper, we discuss the construction of dispatching rules for semiconductor wafer fabrication facilities (wafer fabs) that take equipment health issues into account.

This paper addresses a rich extension of the capacitated vehicle routing problem, which considers sustainability indicators (i.e., economic, environmental and social impacts) and stochastic traveling times. A simheuristic approach integrating Monte Carlo simulation into a multi-start metaheuristic is proposed to solve it.

This article proposes an extension of quality control charts by adding predictive component. This component predicts at which point in time maintenance activities are required based on quality characteristics of the produced work pieces. The article further presents two simulation studies.

In this paper we interpret the historical development of simulation modeling. In our view simulation modeling is that part of the simulation problem-solving process that focuses on the development of the model. It is the interpretation of a real production (or service) problem in terms of a simulation language capable of performing a simulation of that real-world process.

In this tutorial, we explore the definition, requirements and approach to conceptual modeling.

This research focuses on quantifying the dependence of the flow time upon observed job shop status variables, the size of a new order, and the arrival rate of future orders. An iterative fitting procedure based on stochastic kriging with qualitative factors, is developed to synergistically model simulation and real manufacturing data, for the prediction of a new order’s flow time.

This paper illustrates how simulation can be used not only to analyze critical activities and paths, but also to generate the associated survival functions – thus providing the probabilities that the turnaround can be completed before a series of target times.

This paper gives a personal perspective on the evolution of discrete-event simulation – concentrating on how it moved from having an image from the 1950s through the 1980s of being a “brute force programming effort” and as a problem-solving “method of last resort” to today’s status where simulation enjoys “considerable scientific respect.”

This paper presents the history of the Winter Simulation Conference (WSC) for the time period covering 1983–1992. This was a healthy era of growth for WSC as conference attendance was strong, exhibits were added, proceedings became hardback, program tracks were added, the Ph.D. Colloquium was initiated, and the Twenty-Fifth Anniversary of WSC was celebrated in 1992. This article discusses all of the accomplishments for this “Coming-of-Age Period”.

This paper gives the history of verification and validation of discrete-event simulation models as seen through the eyes of its authors and their experiences. The history is divided into three time periods: the early era covering years up to 1970, the awareness era covering the years of the 1970s and 1980s, and the modern era covering the years of 1990 to the present.

This paper discusses the history of the Winter Simulation Conference (WSC) during the period 1975–1982. This includes the collapse of the WSC in 1975, the rebirth of WSC in 1976, and the subsequent annual conferences and other significant WSC events for the period of 1976 through 1982. This was a period of great change for the WSC, with an emphasis on developing procedures to insure the long-term continuity and success of the conference.

This paper discusses the founding of the Computer Simulation Archive at the North Carolina State University Libraries, obtaining the initial contributions to the archive, establishing endowments to support the archive, and forming the Archive Advisory Committee.

In this paper, we present DiSH, a simulator for large discrete models of biological signal transduction path-ways, capable of simulating networks with multi-valued elements in both deterministic and stochastic man-ner. The simulator incorporates the timing of molecular reactions, which are often not synchronized and occur in random order, and it also takes into account the difference between slow and fast reactions.

This paper will present how mechatronic engineering can be developed into an engineering using cyber-physical systems. It will also present how engineering of machine tools and manufacturing systems will change in the future und which concepts can be realized.

This paper deals with the improvement of the robustness of heuristic solutions for aviation systems affected by uncertainty when the resolution of conflicts is implemented. Simulation is used for testing the feasibility of a solution generated by an optimization algorithm in an environment characterized by uncertainty. The results show that the methodology is able to improve solutions for the scenarios with uncertainty, thus making them excellent candidates for being implemented in real environments.

This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; entity lists; and their management. The implementations of these generic ideas in AutoMod, SLX, ExtendSim, and Simio are described. The paper concludes with several examples of “why it matters” for modelers to know how their simulation software works, including discussion of AutoMod, SLX, ExtendSim, Simio, Arena, ProModel, and GPSS/H.

This paper discusses the Origins and Early Years (1967-1974) of the Winter Simulation Conferences. Summary information is given for each of the conferences in that interval, with expanded discussion included for the 1967, 1968, and 1969 formative conferences.

A comprehensive, validated simulation environment is used to analyse the benefits of Side-Slip Seat technology and an adapted boarding strategy is identified using evolutionary algorithms.

This paper discusses stability of demand forecasts depending on time and product granularity and introduces definitions of good and bad stability, using Symmetric Mean Absolute Percentage Error as a measure for stability. We show that time and product granularities have a significant effect on the intra-horizon stability of a demand plan and that planning on different granularities can lead to artificial demand fluctuations at the intersections of planning horizons.

In this paper we discuss the associated modelling issues of a 7-day simulation-based forecast, providing forecast of incoming WIP, moves and utilization at work center level. The simulation forecast consistently achieved an accuracy above 90%.

In this work, we focus on forward-in-time simulations which represent the most powerful, but, at the same time, most computeintensive approach for simulating the genetic material of a population. We present a highly-optimized forward-in-time simulation library called Libgdrift, specially designed to create large sets of replicated simulations. Results show that our proposal can improve the performance reported by well-known simulation software.

This paper introduces a sample average approximation to the continuous distribution problem using methods for solving the discrete distribution problem. We explore using numerical results an example motivated by carbon capture and storage systems.

The following paper describes new empty vehicle management strategies as an important part of this on time automated material handling system delivery. Information about future upcoming transport jobs will be included to allocate this limited resource proactively and to achieve goals such as minimizing the tool waiting time for empty vehicles or the total number of dispatch moves.

This paper and the corresponding panel session focus on teaching undergraduate industrial engineering/operations research-related simulation courses.

This paper details how challenges were overcome and addressed in Captivate with examples, namely display and manipulation of complex expressions and the complexity and length of problems.

This paper provides a case study from the food industry, featuring a comprehensive planning approach based on simulation and optimization. The approach utilizes an offline-coupled multilevel simulation to smooth production and logistics planning via optimization, to optimally configure the production system using discrete-event simulation and to optimize the logistics network utilizing an agent-based simulation.

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In this paper, we propose fundamental abstractions for DELS and identify corresponding libraries of analysis models. These are used in a systemanalysis integration methodology that incorporates abstraction as an explicit step, providing a path to refine and extend those abstractions and model libraries to generate analysis models.

We present a vision towards establishing an automated framework, aimed to enable researchers to construct simulations of refugee movements more quickly and systematically. Our approach incorporates a diverse range of data sources, and uses the FabSim toolkit in conjunction with the Flee simulation code to quickly generate simulation workflows. In addition, we highlight a few key steps that we have already taken towards realizing this vision and discuss opportunities for wider applicability.

In order to reduce transport-related delays before time-critical operations, novel ways of planning wafer transports have been investigated in this study. For validation, a well-known realistic representative wafer fab model has been extended with conveyor elements constituting a typical automated material handling systems for continuous flow transport. As a result, improvements of the overall fab performance due to advanced transport scheduling methods are demonstrated and compared.

The systems considered in this study consist of lightweight shuttle vehicles installed on each level, storing and retrieving lifters, layer conveyors connecting lifters and shuttle vehicles, and incoming and outgoing aisle conveyors. To analyze its performance, simulation models are performed taking the relationships of the storage locations and load sequences into consideration.

This paper proposes a hybrid model of the supply chain (SC) using integration design. It allows the whole SC to be captured at the broad view through system dynamics, and the target firm to be represented using agent-based model.

In this paper, we propose a simulation-based quality variance control system consisted of three core components: an indoor environment calibration module, a quality prediction module and a simulation engine. We then demonstrate the use of this system by analyzing a typical manufacturing process consisted of four sub-processes.

To introduce Open Science to our field, this paper unpacks Open Science to understand some of its approaches and benefits. Good practice in the reporting of simulation studies is discussed and the Strengthening the Reporting of Empirical Simulation Studies standardized checklist approach is presented.

The spherical Monte Carlo estimator is the average of function values of some random points generated by lattice. We consider Value-at-Risk and expected shortfall calculation under heavy-tailed distributions and demonstrate the superiority of the proposed method via numerical studies in terms of variance, computation time, and efficiency.

In this paper, we present an extension of the model alignment methodology for comparing the outcome of two simulation models that searches the response surface of both models for significant differences. Our approach incorporates elements of both optimization and design of experiments for achieving this goal. We discuss the general framework of our methodology, its feasibility of implementation, as well as some of the obstacles we foresee in its generalized application.

Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor – the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor, or SIP, we focus here on its importance to efficient, price discovery. Via extensions to a previous market model, we experiment with four different coupling mechanisms which operate across the US stock market. Of the four, we find that the SIP contributes most to efficient price discovery.

We present a DEVS (Discrete Event System Specification) based framework for modeling a power system for energy planning.

We discuss our experience from helping an airport operator and their team of airport operations analysts to introduce discrete-event simulation alongside their existing system improvement/development toolkit. Our project looked at improving the existing baggage handling system of a major European airport run by our partner organization.

In this paper, it is aimed to improve decision making by increasing the situational awareness of an agent by incorporating the decision making mechanism with the prior knowledge about the problem domain, such as the existing rules. Specifically, an existing adaptive decision making architecture, which is based on the deliberative coherence theory, is adopted to be driven by situational awareness.

To determine the budget needed by a healthcare network to provide government mandated mental health services, a simulation model of those services was built, verified and validated; it was then used to identify where mandated delivery times were not being met and where staff should be reallocated. In addition to the obvious benefits of this approach, a less obvious benefit was that the discovery process needed to build the model identified additional opportunities for providing better care with less resources.

This tutorial introduces the Classic DEVS formalism in a bottom-up fashion, using a simple traffic light example.

This paper delves into each enabler, presenting its relation to Multi-Paradigm Modelling and how it is supported in our prototype tool: the Modelverse. An automotive power window example is used to illustrate the Modelverse’s capabilities. All aspects are explicitly modelled and enacted with a Formalism Transformation Graph + Process Model.

In this piece of research, we attempt to find the optimal time to call for the redistribution of bikes to minimize cost and retain maximum membership.

This paper introduces the locomotive refueling system configuration problem, which arises when railroad companies aim to improve efficiency in refueling yards through new technologies or policies. Results using realistic parameters demonstrate a statistically significant improvement over intuitive policies.

Production Planning and Control has been deeply analyzed in the literature, both in general terms and focusing on specific industries, such as the fashion one. The paper aims to add a contribution in this field presenting an optimization model for the Fashion Supply Chain, developed considering an interdependent environment composed by a group of focal companies that work with both exclusive and not-exclusive suppliers.

We define an operational (transition system) semantics for the two most basic forms of Discrete Event Simulation (DES): event-based simulation (without objects) and object-event simulation. We show that under our operational semantics, DES models correspond to a certain form of abstract state machines (ASMs) such that the Future Event List is part of the transition system state and the transition function is based on event routines.

This tutorial presents a general approach how to use Unified Modeling Language class diagrams and Business Process Modeling Notation process diagrams at all three levels of model-driven simulation engineering: for making conceptual simulation models, for making platformindependent simulation design models, and for making platform-specific, executable simulation models.

The sim4edu.com project website supports web-based simulation with open source technologies for open science and education. It provides both simulation technologies and a library of educational simulation examples. Its aim is to support both the use and the development of various kinds of simulations, including ad-hoc simulations, Cellular Automata models, NetLogo-style grid space models, discrete event simulation and agent-based simulation.

We present a cellular model to study the propagation of cracks in a given sample of rock. The model uses the fractal geometry found in real rocks and the stress and strain on an element of rock to update the element’s strength. We study the propagation speed of the cracks with different initial conditions. The model shows that the more inhomogeneous a rock sample is the quicker a fracture can propagate through it.

We describe an agent-based stock market simulator built using an asynchronous discrete event simulation framework. The simulator is unique in that it’s driven by real-world financial algorithms and protocols; and it’s open source. It utilizes an order book bid and ask matching model, and real-world exchange protocols.

In this paper we propose a novel misspecification test for simulation metamodels. It is a consistent test that helps to assess the adequacy of simulation metamodels.

In this paper, we consider a futuristic scenario where there exists a special lane in a segment of a highway; vehicles which wish to use the lane must send access requests ahead of time; and only the vehicles whose requests are accepted can use the lane.

Mixed type random variables contain both continuous and discrete components, and their role is critical in many well-studied fields. Queuing analysis, stock options, and hydrology rainfall models are among those dependent on mixed random variables to simulate event outcomes. In each of these examples, continuous positive distributions combine with a discrete spike at zero to adequately represent system uncertainty. These problems often require simulation because analytic solutions using these hybrid distributions quickly grow in complexity. This paper details these challenges, and touches on the shifting line between simulations and attainable analytic results.

In this paper, we propose a work-stealing based dynamic load balancing algorithm with the aim of combining their advantages. It adaptively rebalances the LPs distribution based on a priori estimation, and uses a greedy lock-free work-stealing scheme to eliminate bias at runtime.

In this tutorial, we focus principally on discrete-event simulation – its underlying concepts, structure and application.

We describe an approach using discrete event simulation software for assessing the performance and supporting the parameterization of an implant scheduler. Furthermore, rolling-horizon approaches are discussed and the scheduler performance is compared to two dispatch rules.

In this work, we present a network testbed consisting of container-based network emulation and physical devices to advocate high fidelity and reproducible networking experiments.

In this paper we develop a heteroscedastic t-process metamodeling approach (TP) for approximating the mean response surface implied by a stochastic simulation and performing metamodel-based optimization. We provide details on how to construct a TP metamodel, make inference and perform prediction based on TP. We show that TP can retain the attractive properties of approaches that rely on Gaussian processes, but it also enjoys enhanced flexibility, at no additional computational cost.

We illustrate the model structure, flow processing mechanisms, and simulator implementation. We also illustrate the use of this simulator to detect distributed denial-of-service flooding attacks, based on a cross-correlation-based measure. Finally, we show that the layered structure provides new insights on the spatiotemporal spread patterns of cascading failure, by revealing spreads both horizontally within a sub-network and vertically across sub-networks.

To provide a reliable guidance, we propose a simulation calibration framework. We first develop a spatial-temporal metamodel to estimate the system dynamic behaviors at different settings of calibration parameters.

We present a simulation-based scheduling model for Flexible Manufacturing System dynamic shop-floor control. The customer’s order and the processing sequence table of the products are imported into the simulation model. Experiments are implemented for the case wherein the system encounters unexpected conditions. The proposed approach represents a potential tool for manufacturers to make decisions in the real time by further connecting to the enterprise resource planning and manufacturing execution system.

In this paper, surrogate assisted calibration frameworks are proposed to calibrate the crowd model. To integrate the surrogate models into the evolutionary calibration framework, both the offline and online training based approaches are developed.

We put forward a methodological basis, which aims to (1) explore the utility of viewing models as adaptive agents that mediate among domain theories, data, requirements, principles, and analogies, (2) underline the role of cognitive assistance for model discovery, experimentation, and evidence evaluation so as to differentiate between competing models and to attain a balance between model exploration and exploitation, and (3) examine strategies for explanatory justification of model assumptions via cognitive models that explicate coherence judgments.

In this paper we will focus on the application of Simio simulation in the Industry 4.0 environment.

In this paper, we present a simulation model that evaluates health care emergency plan and assesses the resilience of the Ile-de-France region in case of a major flood. We combined in the model the health care process with a Markov chain flood model. The results can be used to elaborate an optimized strategy for evacuation and transfer operations. We provide a case study on three specialties and quantify the impact of several flood scenarios on the health care system.

This paper proposes a concept to model and simulate on- and off-site construction logistics, to facilitate the understanding of the boundary-spanning dependencies of both on- and off-site domains. A framework is provided, including simulation fundamentals (i.e. logistic BIM model), simulation data preparation (i.e. process pattern definition) and implementation of a scenario-based simulation.

In this paper, a SimEvents-based framework is introduced for hybrid traffic simulation at the microscopic level. This framework enables users to apply different control strategies for Connected Automated Vehiclesand carry out performance analysis of proposed algorithms by authoring customized discrete-event and hybrid systems based on MATLAB Discrete-Event System using object-oriented MATLAB. The framework spans multiple toolboxes including MATLAB, Simulink, and SimEvents.

We study a random search algorithm for solving deterministic optimization problems in a black-box scenario. We prove global convergence of the algorithm and carry out numerical experiments to illustrate its performance.

In this paper, we report findings of a simulation study with four causal inference approaches, namely two single tree approaches (transformed outcome tree, causal tree), and two random forest versions of the former.

We model the traffic system as a network of servers that represents both paths and junctions, for which the service rates are dynamically adjusted according to the respective states and decision rules. The model is implemented with O2DES.Net, an open-structured and modularized modeling framework. Numerical experiments illustrate the effectiveness of the developed models, with an application of the AGV network for an automated container terminal.

In this paper, we consider elements of a sustainable and distributed generation system for a wafer fab. Wind turbines (WTs), solar photovoltaics (PVs), a substation with grid access, and a net metering system are included in the generation system. We present results of simulation experiments with the proposed model.

This paper investigates how two well-known improvement approaches, namely lean and simulation-based optimization, can be combined with the concepts of Industry 4.0 to improve efficiency and avoid moving production to other countries.