Discrete Event System Simulation Research Articles

A class of extended time Petri nets for modeling and simulation of discrete event systems

Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems.

Discrete-event system simulation on small and medium enterprises productivity improvement

Small and medium industries in Indonesia is currently developing. The problem faced by SMEs is the difficulty of meeting growing demand coming into the company. Therefore, SME need an analysis and evaluation on its production process in order to meet all orders. The purpose of this research is to increase the productivity of SMEs production floor by applying discrete-event system simulation. This method preferred because it can solve complex problems die to the dynamic and stochastic nature of the system. To increase the credibility of the simulation, model validated by cooperating the average of two trials, two trials of variance and chi square test. Afterwards, Benferroni method applied to development several alternatives. The article concludes that, the productivity of SMEs production floor increased up to 50% by adding the capacity of dyeing and drying machines.

Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation

Time is crucial in the airlines industry. Among all factors contributing to an aircraft turnaround time; passenger boarding delays is the most challenging one. Airlines do not have control over the behavior of passengers; thus, focusing their effort on reducing passenger boarding time through implementing efficient boarding strategies. In this work, we attempt to use cellular Discrete-Event System Specification (Cell-DEVS) modeling and simulation to provide a comprehensive evaluation of aircraft boarding strategies. We have developed a simulation benchmark consisting of eight boarding strategies including Back-to-Front; Window Middle Aisle; Random; Zone Rotate; Reverse Pyramid; Optimal; Optimal Practical; and Efficient. Our simulation models are scalable and adaptive; providing a powerful analysis apparatus for investigating any existing or yet to be discovered boarding strategy. We explain the details of our models and present the results both visually and numerically to evaluate the eight implemented boarding strategies. We also compare our results with other studies that have used different modeling techniques; reporting nearly identical performance results. The simulations revealed that Window Middle Aisle provides the least boarding delay; with a small fraction of time difference compared to the optimal strategy. The results of this work could highly benefit the commercial airlines industry by optimizing and reducing passenger boarding delays.

Application of lean manufacturing principles to improve a conceptual 238Pu supply process

The mission of the United States (U.S.) Department of Energy’s Pu-238 Supply Project is to rebuild capability to produce 238Pu at the kilogram scale in the U.S. This radioisotope is used by the National Aeronautics and Space Administration (NASA) to power deep space probes, and the supply is dwindling. It was last produced in the U.S. in 1988. A conceptual design of a 238Pu supply process is described that uses existing processes and facilities at Oak Ridge National Laboratory’s Radiochemical Engineering Development Center. The rate-limiting section of the conceptual process was analyzed using discrete-event system simulation to determine expected production rates, bottlenecks, and the effects of time delays on the production rate. Process alternatives were generated based on Lean Manufacturing principles, and those were examined and compared to the original process using simulation to identify better operating strategies.

Ururau: a free and open-source discrete event simulation software

This paper has the purpose of describing the architecture and operation of Ururau, a software used to create discrete event simulation models based on the Java Simulation Library. Ururau is a free and open-source multiplatform software, which allows the user to develop models in the graphical interface or implement them directly in the source code. This characteristic allows the user to employ it as a tool for modeling and simulation of discrete event systems and also as a learning tool. Thus, an experienced modeler can add specific algorithms to simulation models or new features to the simulator. Also, with access to the source code, a beginner modeler can understand the internal structure of a discrete event simulation software. Initial results have demonstrated this new software’s ability in building small and simple models efficiently.

Computational speed and high-frequency trading profitability: an ecological perspective

High-frequency traders (HFTs) account for a considerable component of equity trading but we know little about the source of their trading profits and to what extend IT based differentiators such as news processing power and ultra-low latency has contributed to competitive advantage within HFT realm. Given a fairly modest amount of empirical evidence on the subject, we study the effects of computational speed on HFTs’ profits through an experimental artificial agent-based equity market. Our approach relies on an ecological modelling inspired from the r/K selection theory, and is designed to assess the relative financial performance of two classes of aggressive HFT agents endowed with dissimilar computational capabilities. We use a discrete-event news simulation system to capture the information processing disparity and order transfer delay, and simulate the dynamics of the market. Through Monte Carlo simulation we obtain in our empirical setting robust estimates of the expected outcome.

Analysis of the integration between operations management manufacturing tools with discrete event simulation

The purpose of this paper is to analyse the integration of discrete event simulation (DES) in operations management manufacturing tools. Due to the movement of the fourth industrial revolution (Industrie 4.0), the integration of manufacturing is a topic constantly discussed in many areas. Moreover, it presents great research and innovation opportunities. To achieve the objective of this study, a search was conducted using the main keywords found in papers related to manufacturing systems and operations management manufacturing tools. Also, academic databases were literature research to identify the keywords relevant to the study added to DES. We considered only articles from the last 8 years. At the end between the search, the integration between tools such as manufacturing execution system, enterprise resource planning, radio frequency identification, core manufacturing simulation data, e-Kanban with DES were analysed. Furthermore, it was observed that the tools cannot always be used separately, but in some cases, these tools should be used jointly to solve problems related to production systems. Another aspect observed was how the data collected in production systems are fed to the DES models. Through, it was possible to analyse an existing gap regarding how the data is used between DES and manufacturing systems, thereby enabling research development in this area.

A non-queue-based paradigm in Discrete-Event-Simulation modelling for construction operations

Discrete-Event Simulation (DES) is an event-driven simulation approach in which a real dynamic process is imitated as it progresses over time. It has been recognized as a powerful technique for the quantitative analysis of complex construction operations. However, current DES modelling strategies/frameworks implicitly rely on queuing structures which are too rigid to easily describe systems with complex behaviour common in construction, e.g., multi-tasking resources and/or role changes of entities. Queuing networks are one of the most common elements of DES systems and have been used to model a wide range of problems, but they lack the generality to easily model the complex decision mechanisms required to, e.g., efficiently multi-task or dynamically determine the best role for an entity. This research proposes a new modelling approach for construction that replaces Queue-Based (QB) DES, with its implicit queuing network control, with Non-Queue-Based (NQB) DES that explicitly defines the decision mechanisms of a model. It utilises a new conceptual modelling paradigm for simulation, Hierarchical Control Conceptual Modelling, which was developed to address similar issues with control mechanisms in health care simulation. This new approach is especially beneficial for the construction industry where determining effective decision making mechanisms is of significant importance for optimising, e.g., logistics and resource utilisation. This research investigates the benefits of the proposed approach for DES models in construction by investigating three earthmoving case studies. Although the scope of this research is limited to DES modelling in construction, the outcomes of the proposed NQB paradigm in construction translate to other domains that utilise DES for solving complex problems.

Unified behavior framework in discrete event simulation systems

Intelligent agents provide simulations a means to add lifelike behavior in place of manned entities. When implemented, typically a single intelligent agent model (or approach to defining decision making), such as rule-based, behavior trees, neural networks, etc., is selected. This choice introduces restrictions into what behaviors agents can manifest, and can require significant testing in edge cases. This paper presents the incorporation and application of the Unified Behavior Framework (UBF) into the Advanced Framework for Simulation, Integration, and Modeling environment. The UBF provides the flexibility to implement any and all behavior-based systems, allowing the developer to rapidly assemble a decision making agent that leverages multiple paradigms or approaches. The UBF achieves this by leveraging several key software engineering principles: modular design, scalability through reduced code complexity, simplified development and testing through abstraction, and the promotion of code reuse. The use of UBF to define intelligent agents within a 2v2 Integrated Air Defense System is demonstrated.

DEv-PROMELA: an extension of PROMELA for the modelling, simulation and verification of discrete-event systems

PROMELA is a well-known formalism for the modelling and the verification of concurrent systems. PROMELA deals with high-level specifications. As a result, PROMELA models are expressed in a high-level abstraction which does not consider explicit representation of time or events for example. But, the efficiency of the processes of verification and validation relies on the accuracy of the models. That is why we propose, in this paper, work to develop a new extension of PROMELA for the modelling of discrete-event systems. The verification of these models is then done by combining formal verification and simulation-based verification using SPIN and the tool DEv-PROMELA Studio, or using any existing DEVS simulators.

DEv-PROMELA: an extension of PROMELA for the modelling, simulation and verification of discrete-event systems

DEv-PROMELA: an extension of PROMELA for the modelling, simulation and verification of discrete-event systems

Simulation of Electrical Grid with Omnet++ Open Source Discrete Event System Simulator

Abstract The simulation of electrical networks is very important before development and servicing of electrical networks and grids can occur. There are software that can simulate the behaviour of electrical grids under different operating conditions, but these simulation environments cannot be used in a single cloud-based project, because they are not GNU-licensed software products. In this paper, an integrated framework was proposed that models and simulates communication networks. The design and operation of the simulation environment are investigated and a model of electrical components is proposed. After simulation, the simulation results were compared to manual computed results.

Hospital Event Simulation Model: Arrivals to Discharge–Design, development and application

In this paper we outline the design, development and application of a hospital patient flow management support tool – Hospital Event Simulation Model: Arrivals to Discharge (HESMAD). The model captures the patterns of patient flows within Flinders Medical Centre, a teaching hospital located in South Australia, through extensive exploitation of an existing hospital patient journey database (PJD). HESMAD employs mathematical and statistical modelling techniques, as well as the concept of modular design, to construct functions and processes that are embedded in a discrete event simulation system. The current structure of HESMAD reflects many iterations of refinements based on feedback from relevant industry experts. It places great emphasis on providing an engaging visualisation of the dynamics of events, and a convenient interface for domain experts: doctors, hospital managers and other health care professionals. An illustrative example of HESMAD’s wider applicability is presented.

Integration of scheduling and discrete event simulation systems to improve production flow planning

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Advanced approach to assess and improve underground mine evacuation using discrete-event simulation and animation

An advanced approach is presented to use discrete-event system simulation for a better evaluation of various configurations for emergency evacuation operations in underground mines. The mine system evacuation simulation (MSES) models are introduced and demonstrated as a powerful and cost-effective tool for improving emergency response protocols/procedures and planning rescue equipment in underground mine operations. These simulation and animation models can assist mining personnel, rescue teams, and engineers in designing, training, and investigating a wide range of 'what if?' questions in both rescue and evacuation attempts in case of disasters or mine emergencies. A simulation model of an underground metal mine with an animation interface was developed using GPSS/H® and Proof Professional®, discrete-event system simulation and animation programs, to analyse the mine's emergency evacuation plans. The simulation results provided realistic estimates of mine evacuation times for different scenarios under certain circumstances.

Using Discrete-Event Simulation Systems as Support for Production Planning

In the days of fierce competition, rapid changes and new technologies, production, and above all, production planning and control cannot be implemented in isolation to changes in the market. The ability to quickly adjust to changes, being flexible is now essential for high tech companies. One of the key area of production management, that must continuously evolve by searching for new methods and tools for increasing the efficiency of decision-making process is the area of production planning and control. In solving the problems associated with production planning are increasingly used advanced simulation programs. They support the planners, especially in situations related to changes in the assortment, or the introduction of new products into the market. A practical example of using the simulation program for production planning is presented in the paper. It is shown that an advanced simulation program can be an effective tool used in decision making area. The construction of the model, and performed experiments are crucial for enterprises where among other things punctuality and flexibility are the most important elements. A short time for the results of the simulation allows for quick response and, if necessary, make changes to the model by planners to achieve the best results with the given parameters associated with the required to complete the production orders.

Action-level real-time DEVS modeling and simulation

For some classes of systems, it is advantageous to develop real-time models instead of step-wise or logical-time models. Toward this goal, the action-level real-time (ALRT) discrete-event system specification (DEVS) modeling and simulation approach is proposed. Modeling of actions is introduced into the parallel DEVS formalism using time invariants defined for real-time statecharts. Actions are specified in terms of time-windows that are to be executed in real-time. An abstract simulator protocol is devised for executing the ALRT-DEVS models under constrained computational resources. The approach is implemented in the parallel DEVS-Suite simulator. These models can be simulated on unitary computing platforms. A simple example switch model is detailed and tested to show the kinds of real-time modeling and simulation studies that can be supported.

Simulation and animation model to boost mining efficiency and enviro-friendly in multi-pit operations

A discrete-event system simulation and animation program was developed to enhance the efficiency of a truck-excavator operation and reduce the environmental impact of haulage in an open-cut coal mine with multiple-pit operations. In any mine, a key objective is to have sufficient equipment for production and not to have excess to where it becomes counterproductive. Due to the advent of responsible mining, environmental regulations, and eco-friendly practices, these factors must also be considered in the analysis. Simulation studies can be financially advantageous for both the optimization of existing mine operations and new development phases in a mine. This study is a new approach to use discrete-event system simulation for mine systems, in order to investigate and possibly reduce environmental impact considering mining haulage performance and production target. A hypothetical layout of a surface coal mine with two pit operations was used for the simulation and animation model. The simulation model includes the animation of the operation. Animation is helpful to enhance the benefit of a mine simulation model. GPSS/H® and Proof Professional® were the software used for the investigation.

An ant colony optimization approach for solving an operating room surgery scheduling problem

Operating room surgery scheduling deals with determining operation start times of surgeries on hand and allocating the required resources to the scheduled surgeries, considering several constraints to ensure a complete surgery flow, the resource availability, and specialties and qualifications of human resources. This task plays a crucial role in providing timely treatments for the patients while ensuring the balance in the hospital’s resource utilization. By observing similarities between operating room surgery scheduling and a multi-resource constraint flexible job shop scheduling problem (FJSSP) in manufacturing, this article proposes an Ant Colony Optimization (ACO) approach to efficiently solve such surgery scheduling problems based on the knowledge gained in FJSSP. Numerical experiments are performed on five surgery test cases with different problem sizes and resource availability. The performance of the ACO algorithm was compared against schedules generated by a discrete event system simulation model built in SIMIO on five test cases. The results showed a superior performance of ACO in makespan, overtime, and the variation coefficient of working time.

Holistic modelling for human-autonomous system interaction

For complex systems that embed automation, but also rely on human interaction for guidance and contingency management, holistic models are needed that provide for an understanding of the individual human and computer elements, and address the critical interactions of such complex systems. Discrete event simulation (DES) models and system dynamics (SD) models are two different approaches that can be used to address these requirements. Both modelling approaches can support the designers of future autonomous vehicle (AV) systems by simulating the impact of alternate designs on vehicle, operator, and system performance. However, the DES modelling approach is likely best suited for using probabilistic distributions to accurately model an operator who is a serial processor of discrete tasks, as well as an environment with randomly occurring events. The SD modelling approach is better suited for modelling continuous performance feedback that is temporally dependent and is affected by qualitative variables such as trust.