QOBJ modeling: A new approach in discrete event simulation

This paper deals with a new discrete event simulation modeling concept, calledqobj, which comes from two well-known paradigms:objects andqueuing networks. The first provides important conceptual tools for model organization, while the second one allows for nice visualization of models' internal state and processes. Thanks to the integration of these two paradigms, theqobj concept allows the suppression of several dichotomies characterizing current simulation modeling approaches. For instance,qobj allows the description of system elements which are both mobile and able to do processing, and allows the dynamic instantiation of static and mobile elements during simulation. The design of lift group models for an industrial project illustrates the main features of theqobj concep

Load sharing for optimistic parallel simulations on multicore machines

Parallel Discrete Event Simulation (PDES) is based on the partitioning of the simulation model into distinct Logical Processes (LPs), each one modeling a portion of the entire system, which are allowed to execute simulation events concurrently. This allows exploiting parallel computing architectures to speedup model execution, and to make very large models tractable. In this article we cope with the optimistic approach to PDES, where LPs are allowed to concurrently process their events in a speculative fashion, and rollback/ recovery techniques are used to guarantee state consistency in case of causality violations along the speculative execution path. Particularly, we present an innovative load sharing approach targeted at optimizing resource usage for fruitful simulation work when running an optimistic PDES environment on top of multi-processor/multi-core machines. Beyond providing the load sharing model, we also define a load sharing oriented architectural scheme, based on a symmetric multi-threaded organization of the simulation platform. Finally, we present a real implementation of the load sharing architecture within the open source ROme OpTimistic Simulator (ROOT-Sim) package. Experimental data for an assessment of both viability and effectiveness of our proposal are presented as well. Copyright is held by author/owner(s)

Manufacturing System Lean Improvement Design Using Discrete Event Simulation

Lean manufacturing (LM) has been used widely in the past for the continuous improvement of existing production systems. A Lean Assessment Tool (LAT) is used for assessing the overall performance of lean practices within a system, while a Discrete Event Simulation (DES) can be used for the optimization of such systems operations. Lean improvements are typically suggested after a LAT has been deployed, but validation of such improvements is rarely carried out. In the present article a methodology is presented that uses DES to model lean practices within a manufacturing system. Lean improvement scenarios are then be simulated and investigated prior to implementation, thereby enabling a systematic design of lean improvements

Simulation modelling and strategic change : creating the sustainable enterprise

Peer reviewedPublisher PD

Collaborative information systems and business process design using simulation

The Information Systems (IS) community promotes the idea that IS analyst should have a clear understanding of the way the organization operates before attempting to propose an IS solution. It is argued that to take a complete advantage of the underlying Information Technology (IT), organizations should first identify any process flaw and then propose a suitable IT solution. Similarly, many process design approaches claim that Business Process (BP) design should be done considering the advantages provided and the limitations imposed by the underlying (IT). Despite this fact research in these domains provides little indication of which mechanisms or tools can help BP and IS analyst to understand the complex relationships amongst these two areas. This paper describes the insights gained during a UK funded research project, namely ASSESS-IT, that aimed to depict the dynamic relationships between IT and BP using simulation. One of the major limitations of the ASSESS-IT project is that it looked at relationship between BP and IT as a three layered structure, namely BP, IS and Computer Networks (CN), and did not explore in detail the relationships between BP and IS alone. This paper uses the outcomes derived from this project and suggests that, is some cases, the relationship between BP and IT could be analyzed by looking at the relationship between BP and IS alone. It then proposes an alternative simulation framework, namely BPISS, that provides the guideline to develop simulation models that portray BP and IS behavior performance measurements, offering in this way an alternative mechanism that can help BP and IS analyst to understand in more detail the dynamic interactions between BP and IS domains

Investigating biocomplexity through the agent-based paradigm.

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update