COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Abstract Simulation models of the software development process can be used to evaluate potential process changes. Careful evaluation should consider the change within the context of the project environment. While system dynamics models have been used to model the project environment, discrete event and state-based models are more useful when modeling process activities. Hybrid models of the software development process can examine questions that cannot be answered by either system dynamics models or discrete event models alone. In this paper, we present a detailed hybrid model of a software development process currently in use at a major industrial developer. We describe the model and show how the model was used to evaluate simultaneous changes to both the process and the project environment. <s> BIB001 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Hierarchical production planning provides a formal bridge between long-term plans and short-term schedules. A hybrid simulation-based production planning architecture consisting of system dynamics (SD) components at the higher decision level and discrete event simulation (DES) components at the lower decision level is presented. The need for the two types of simulation has been justified. The architecture consists of four modules: enterprise-level decision maker, SD model of enterprise, shop-level decision maker and DES model of shop. The decision makers select the optimal set of control parameters based on the estimated behavior of the system. These control parameters are used by the SD and DES models to determine the best plan based on the actual behavior of the system. High level architecture has been employed to interface SD and DES simulation models. Experimental results from a single-product manufacturing enterprise demonstrate the validity and scope of the proposed approach. <s> BIB002 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Multi-plant production planning problem deals with the determination of type and quantity of products to produce at the plants over multiple time periods. Hierarchical production planning provides a formal bridge between long-term plans and short-term schedules. A hybrid simulation-based hierarchical production planning architecture consisting of system dynamics (SD) components for the enterprise level planning and discrete event simulation (DES) components for the shop-level scheduling is presented. The architecture consists of the Optimizer, Performance Monitor and Simulator modules at each decision level. The Optimizers select the optimal set of control parameters based on the estimated behaviour of the system. The enterprise-level simulator (SD model) and shop-level simulator (DES model) interact with each other to evaluate the plan. Feedback control loops are employed at each level to monitor the performance and update the control parameters. Functional and process models of the proposed architecture... <s> BIB003 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions, engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on either system performance or product performance. In this paper, we focus on the impact of production decisions, evaluated using discrete-event-simulation models, on enterprise-level performance measures. We argue that these discrete-event models alone are not enough to capture this impact. To address this problem, we propose integrating discrete-event simulation models with system dynamics models in a hybrid approach to the simulation of the entire enterprise system. This hybrid approach is conceptually consistent with current business trend toward integrated systems. We show the potentials for using this approach through an example of a semiconductor enterprise. <s> BIB004 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Simulations have significantly contributed to the analysis of construction, and Discrete Event Simulation has been a primary means of simulation focusing on Construction Operation. In this paper, the authors address the importance of Construction Context as another realm for understanding and managing construction through representation of overall behavior of construction associated with Construction Operation. The issues raised from representing both Construction Operation and Construction Context together in a simulation model are discussed, and a hybrid System Dynamics and Discrete Event Simulation approach is proposed as a comprehensive simulation framework for that purpose. Briefly, its application to construction is also discussed. <s> BIB005 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Healthcare organizations exhibit both detailed and dynamic complexity. Effective and sustainable decision-making in healthcare requires tools that can comprehend this complexity. Discrete event simulation (DES) due to its ability to capture detail complexity is widely used for operational decision making. However at the strategic level, System Dynamics (SD) with its focus on a holistic perspective and its ability to comprehend dynamic complexity has advantages over DES. Appreciating the complexity of healthcare, the authors have proposed the use of hybrid simulation in healthcare. As argued previously, effective decision making require tools which are capable of comprehending both detail and dynamic interactions of healthcare. The interactions in the organizations are governed by the governance design. In appreciation of that argument the authors have described the applicability of a hybrid approach to various modes of governance in UK healthcare. <s> BIB006 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> A significant number of large-scale civil infrastructure projects experience cost overruns and schedule delays. To minimize these disastrous consequences, management actions need to be carefully examined at both the strategic and operational levels, as their effectiveness is mainly dependent on how well strategic perspectives and operational details of a project are balanced. However, current construction project management approaches have treated the strategic and operational issues separately, and consequently introduced a potential conflict between strategic and operational analyses. To address this issue, a hybrid simulation model is presented in this paper. This hybrid model combines system dynamics and discrete event simulation which have mainly been utilized to analyze the strategic and operational issues in isolation, respectively. As an application example, a nontypical repetitive earthmoving process is selected and simulated. The simulation results demonstrate that a systematic integration of strategic perspective and operational details is helpful to enhance the process performance by enabling construction managers to identify potential process improvement areas that traditional approaches may miss. Based on the simulation results, it is concluded that the proposed hybrid simulation model has great potential to support both the strategic and operational aspects of construction project management and to ultimately help increase project performance. <s> BIB007 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Construction systems and projects comprise complex combinations of subsystems, processes, operations, and activities. Discrete Event Simulation (DES) has been used extensively for modeling construction systems, addressing system complexity, and analyzing system behavior. However, while DES is a powerful tool for capturing operations as they occur in reality, DES does have difficulty modeling context and its mutual effects on the operational components of a system. System Dynamics (SD), on the other hand, captures feedback loops that are derived from the context level of a system and that can anticipate system behavior; nevertheless, SD cannot effectively model the operational parts of a system. Hybrid SD and DES modeling provide a set of tools that use the capabilities, while improving upon the disadvantages, of these two approaches. Although initial efforts to develop hybrid SD-DES modeling dates back to the late 1990s, in the construction industry, there are relatively few studies in this area, and there is still no robust architecture for hybrid system developers. This paper addresses these issues by proposing a comprehensive hybrid simulation architecture based on the High Level Architecture (HLA) infrastructure, which can be used by hybrid simulation developers in the construction industry. A typical steel fabrication shop has been modeled based on the proposed architecture, and it has been compared with the ideally developed hybrid simulation architecture. <s> BIB008 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> Especially in the European Union both, regulatory requirements regarding the CO2 emissions of new vehicles and the shortage of crude oil force car manufacturers to introduce alternative fuel and powertrain concepts. Due to high investments and long development times as well as the parallel offer of conventional and alternative technologies, an appropriate product strategy is required. Car manufacturers have to decide, which powertrain to introduce at which time in which vehicle class. Hence, the aim of this paper is to develop a framework for the analysis of product strategies in the automotive industry with special regard to alternative fuel and powertrain technologies. The framework integrates System Dynamics and Agent-based Simulation in a simulation environment. On basis of this analysis recommendations can be deduced concerning the implementation of different product portfolios. <s> BIB009 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> We build a hybrid discrete-continuous simulation model of the manufacturing enterprise system. This model consists of an overall system dynamics model of the manufacturing enterprise and connected to it are a number of discrete event simulations for selected operational and tactical functions. System dynamics modeling best fits the macroscopic nature of activities at the higher management levels while the discrete models best fit the microscopic nature of the operational and tactical levels. An advanced mechanism based on information theory is used for the integration of the different simulation modeling modalities. In addition, the impact of the decisions at the factory level in scheduling are analyzed at the management level. The different models of control are discussed. <s> BIB010 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> Area/industry of application <s> The idea of combining discrete-event simulation and system dynamics has been a topic of debate in the operations research community for over a decade. Many authors have considered the potential benefits of such an approach from a methodological or practical standpoint. However, despite numerous examples of models with both discrete and continuous parameters in the computer science and engineering literature, nobody in the OR field has yet succeeded in developing a genuinely hybrid approach which truly integrates the philosophical approach and technical merits of both DES and SD in a single model. In this paper we consider some of the reasons for this and describe two practical healthcare examples of combined DES/SD models, which nevertheless fall short of the "holy grail" which has been so widely discussed in the literature over the past decade. <s> BIB011
In the manufacturing industry, there is a good example for modelling hierarchical production systems BIB002 BIB003 . The authors are concentrated on the production and production related elements, and have developed a SD model for the long-term plans (developed by the "Enterprise-level decision maker") and short-term plans (developed by the "Shop-level decision maker"). In the paper BIB004 ) the authors have also examined a manufacturing enterprise, where they used SD to simulate a financial (reinvestment) policy and DES to simulate the production process of one machine. They have represented the number of machines in the SD model, so by "multiplying" this variable with the output of the DES process they can generate the production output of the enterprise. Based on the framework of  ), same has been tested and a hierarchical production model has been developed BIB010 ). In the recent decade, the healthcare management has been seen as a very interesting field for the industrial engineers (the Institute of Industrial Engineers <www.iienet.org> have classified Healthcare Management in the same importance as Lean & Six Sigma, Supply Chain Management, Ergonomics, Quality systems etc. and some universities have a special IE curriculum for Healthcare management, e.g. TU Eindhoven <www.tue.nl>). This interest has also been shown in using the simulation for tackling issues in the healthcare. BIB006 have distinguished three formats how the models inside a hybrid mode can communicate: Hierarchical, Process-Environment and Integrated format. Later they have suggested a framework for hybrid simulation in the healthcare  . In the work of BIB011 the authors used the hybrid models to represent two case. The first one is when the DES model simulates a process of a patient being examined with a whole configuration of a hospital, while the SD simulates the community and how a specific disease would spread. In the second case, the DES was used to simulate operations of a contact centre, and SD to simulate demographic changes of the population being examined. The use of hybrid modelling has found its applicability in the civil engineering as well BIB007 BIB005 ; BIB008 ) dealing with problems that are more complex to be solved with independent simulation models or project management tools. One of the few advantages that the authors found with this approach is the benefit of proposals for improvement they got from the models. In the same direction as the previous two papers, BIB001 have also suggested a hybrid approach in the software industry. They have worked on an issue that can be managed with project management software as well, but they argue that the benefit of the hybrid simulation is the experimentation that can be done. The use of agent-based modelling and SD as hybrid architecture can be also adapted for the automotive industry BIB009 ).