Traditional Discrete Event Research Articles

Discrete event simulation and Digital Twins in warehouse logistics: a bibliometric and content analysis-based systematic literature review

ABSTRACT In Warehouse Logistics (WL), the growing adoption of Industry 4.0 automations coupled with the demand for efficient and almost instantly responsive decision-making has already created a paradigm shift from the traditional Discrete Event Simulation (DES) models into innovative new ones utilizing the inherent functionalities of ‘Digital Twins’ (DTs), one of today’s most disruptive Industry 4.0 technologies. DTs are ‘real-world aware’ through the creation of exact software replicas of actual systems, allowing the convergence of physical and virtual entities and facilitating real-time responsive decision-making. In this paper, a bibliometric and content analysis-based systematic literature review is performed to explore the adoption, implementation and evaluation of DES and DTs in WL. The authors focus on how and to what extent these two methods are integrated into the various WL theoretical and real-life applications to enhance a plethora of performance factors as well as look into their exploitation, as standalone solutions or in tandem with one another and other modelling and simulation approaches, technologies, algorithms, methods, methodologies and strategies in different contexts and environments. Based on the review results, a conceptual framework is proposed combining the multiple perspectives examined, contributing to the systematization and standardization of the field and pinpointing future research directions.

Agents and Events: the Objective of Action, Finite Event Duration, and Fuzzy Logic

In a traditional discrete event and queuing simulation the user defines the system resources and the possible events that the model entities (clients, moving items) will execute. In the proposed approach the entities are replaced with agents which actions are not pre-defined and rather result from the agent objectives. The resulting events are also equipped with sub-objectives to reach. The goal of this paper is to propose an event simulation paradigm, different from the traditional crisp discrete event simulation. This is a methodological and conceptual approach, rather than a practical implementation. The proposed approach is to equip the events interactions with finit duration and fuzzy logic. It is pointed out that the problem of handling of simultaneous events does not exist in such models. It is also shown that the classic crisp discrete event model is not necessarily the limit case of any sequence of semi-discrete models with event duration interval approaching zero.

A modelling and simulation study of a metro line as a time-delayed switched system

In public transportation systems, there is a linear relationship between the passenger quantities in a station and the headway of the vehicles. An optimized headway is beneficial for both passenger satisfaction and cost reduction, since reducing the headway will increase operational costs. The headway update starts from the first station and propagates to the other stations with a time delay, τ, originating from the train's travel time between the first station and the affected station. A well-defined model of the passenger quantities in the transportation line is required for tuning the headway efficiently. In this study, the transportation system is considered as a switched time-delayed system since the change in passenger quantities is dependent on the state of a train arriving at the station and travel time is a pure delay between stations. A sample metro line has been modelled as a switched time-delayed system and simulated on MATLAB Simulink® utilizing real-world data provided by Metro Istanbul. The results of the simulations of this new model have been compared to the traditional discrete event simulations of the Arena®. Both results were consistent and the simulation based on our switched time-delayed system mathematical model was significantly faster and dynamically adjustable.

Semi-discrete events with fuzzy logic

Models with events that have small non-zero duration are considered. The goal of this paper is to propose an event simulation paradigm, different from the traditional crisp discrete event simulation. This is a methodological and conceptual approach, rather than a practical implementation. Some issues related to simultaneous event treatment in the classic discrete event simulation are addressed. The proposed approach is to equip the events interactions with fuzzy logic and introduce events with finite duration instead of those executed in discrete time instants. It is pointed out that some difficulties that arise while handling simultaneous events do not exist in models with events of finite duration.

Validation of the finite state machine model for network simulation and a proposed testbed

Under the Cyber Army Modeling and Simulation (CyAMS) program a new model has been created to efficiently model various cyber events. The finite state machine model allows for the modeling of applications by creating behaviors that map to properties of real world applications. The finite state machine model is originally implemented by utilizing the ns-3 parallel discrete event simulator and validated using data from an emulation testbed experiment featuring malware applications. Following the completion of the ns-3 validation work, the CyAMS behavioral simulator was developed to allow for larger scale networks to be modeled, while also allowing both the network and applications to be defined using a behavioral network. This allows for the creation of an accurate mapping between both the simulation and the emulation applications. Validation tests are then carried out to determine both the validity of the model and the potential scalability. Finally, a testbed is proposed that will combine behavioral simulation, traditional parallel discrete event simulation, and emulation. The creation of this end-to-end environment for cyber simulation will allow past, present, and potentially future cyber events to be modeled in order to help understand and potentially mitigate future malicious attacks.

Seven Obstacles in the Way of Standard-Compliant Parallel SystemC Simulation

The IEEE 1666-2011 standard defines SystemC based on traditional discrete event simulation (DES) and sequential co-routine semantics, despite explicit parallelism in the model and ample parallel processor cores available in today’s host computers. In order to evolve the SystemC standard toward faster parallel DES, substantial hurdles must be overcome. This letter identifies seven obstacles in the standard that stand in the way of efficient parallel SystemC simulation, namely the co-routine semantics, simulator state, lack of thread safety, the role of channels, TLM-2.0, sequential mindset, and temporal decoupling. For each obstacle, we discuss the problem and propose a potential solution toward truly parallel SystemC. This letter to the editor is meant to identify difficulties with IEEE SystemC and stimulate fruitful discussion in the community.

Modelling Reactive and Proactive Behaviour in Simulation

This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the operation system of a fitting room in WomensWear department was investigated. We have looked at ways to determine the efficiency of new management policies for the fitting room operation through simulating the reactive and proactive behaviour of staff towards customers. Once development of the simulation models and their verification had been done, we carried out a validation experiment in the form of a sensitivity analysis. Subsequently, we executed a statistical analysis where the mixed reactive and proactive behaviour experimental results were compared with some reactive experimental results from previously published works. Generally, this case study discovered that simple proactive individual behaviour could be modelled in both simulation models. In addition, we found the traditional discrete event model performed similar in the simulation model output compared to the combined discrete event and agent based simulation when modelling similar human behaviour.

Developing service supply chains by using agent based simulation

Purpose – Agent-based computer simulation gives new possibilities to model service supply chains which combine flow of people, geographical elements, demand patterns and service rates. The purpose of this paper is to demonstrate by using an example how agent-based modeling can be used for health service supply chain design. Design/methodology/approach – Generic structure of agent-based service supply chain modeling is described. The presented example is healthcare supply chain with service distribution and service location problem. Main focus in presentation on model building, actual case data are not discussed. Findings – In context of service supply chain, agent-based modeling has advantages compared to traditional discrete event approach. Agent-based simulation allows modeling of interactions of autonomous agents. Practical implications – Reach of service for each geographical area may be used as a constraint for building service distribution network. Service supply chains consist of service providers ...

Simulation-Based Approach for Estimating Project Completion Time of Stochastic Resource–Constrained Project Networks

This paper proposes a new approach, entitled discrete event simulation with probabilistic event list (DESPEL), for approximating the project completion time and the critical path in a stochastic resource–constrained project network. Unlike the traditional discrete event simulation approach, which is based on replications to find the project completion time, this approach only requires one simulation run. This approach is similar to the program evaluation and review technique (PERT) approach in the sense that it considers the path with the highest expected activity duration as the critical path. However, it extends the capability of the PERT by considering the resource constraints when finding the critical activities and project completion time.

Modeling the Lanchester Laws with System Dynamics

This study develops a framework using the Lanchester Laws in a hybrid system dynamics model. Two models of the Lanchester Laws are compared. The first is a traditional discrete event simulation and the other is a system dynamics model. System dynamics models are able to represent qualitative aspects of combat that are difficult to capture in a discrete event simulation. This is directly applicable to modeling combat since some key drivers within the expected environment are difficult to model. Additionally, the system dynamics construct allows for the modeling of continuous events and incorporating system feedback. Both of these properties are favored when modeling combat or asymmetrical operations. Results from the discrete event simulation and the system dynamics model are analyzed and contrasted.

Solution Approaches to Real-time Control of Customized Mass Production

The paper summarises the main challenges and problems related to customised mass production. In the elaborated solution the reference for real-time production control is generated by a novel scheduling system. Detection of changes and disturbances emerging during the daily production is based on the integration of information coming from the process, quality and production monitoring subsystems. All the information forms the basis of rescheduling policies. In the proposed framework both the more traditional discrete event simulation (in different settings) and the agent-based approach plays key role. The effectiveness of the proposed solutions is shown by experimental results on industrial data.

NetScale

This paper presents a scalable time-stepped hybrid simulation algorithm which is well adapted to the simulation of large IP networks (up to one million of competing ows and network elements), while tracking reactive traffic behaviour and packet-level phenomena e.g. timeout trigger or packet burstiness. This simulation paradigm allows one to gain several orders of magnitude of computation time compared to traditional discrete event simulation approaches. The accuracy of this simulation method is evaluated by comparison to other simulation methodologies. Examples of large scale network simulations are also presented.