COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> SYSTEM DYNAMICS <s> More efficient and effective control of supply networks is conservatively worth billions of dollars to the national and world economy. Developing improved control requires simulation of physical flows of materials involved and decision policies governing these flows. We describe our initial work on modelling each of these flows as well as simulating their integration through the synchronized interchange of data. We show the level of abstraction that is appropriate, formulate and test a representative model, and describe our findings and conclusions. <s> BIB001 </s> COMBINING SYSTEM DYNAMICS AND DISCRETE EVENT SIMULATIONS - OVERVIEW OF HYBRID SIMULATION MODELS <s> SYSTEM DYNAMICS <s> This article proposes an approach to a hybrid software process simulation modeling (SPSM) using discrete event system specification (DEVS) formalism, which implements the dynamic structure and discrete characteristics of the software development process. Many previous researchers on hybrid SPSM have described both discrete and continuous aspects of the software development process to provide more realistic simulation models. The existing hybrid models, however, have not fully implemented the feedback loop mechanism of the system dynamics. We define the DEVS Hybrid SPSM formalism by extending DEVS to the hybrid SPSM domain. Our hybrid SPSM approach uses system dynamics modeling to convey details concerning activity behaviors and managerial policies, while discrete event modeling controls activity start/completion and sequence. This approach also provides a clear specification, an explicit extension point to extend the simulation model, and a reuse mechanism. We will demonstrate a Waterfall-like hybrid software process simulation model using the DEVS Hybrid SPSM formalism. Copyright  2006 John Wiley & Sons, Ltd. <s> BIB002
System Dynamics (SD) is a relatively new technique that has been populated in the last 20 years. The basic principle underlying system dynamics is that the structure of a system determines its behaviour over time   . SD is all about the whole and looking at the system as a unit. In normal cases, a lot of people use the divide-andconquer system in order to solve complex problems. The philosophy of SD is that every element is connected somehow with other element(s) and those relationships determine how the system performs over time. It is best used when modelling very complex systems that are very hard to perceive and understand. There are two main approaches that help define a SD model. The first one is the causal loops (and feedback loops), which are widely spread and very useful. Most of the time, they are the first step in developing a SD model, helping in the conceptualisation. The second tool is the stock and flow diagrams, which aid to describe the model using data. The easiest way to describe this is to think of models like system of water tanks with pipes and valves  . In the research conducted by  they have stated that "using SD at the operational level of the manufacturing system has failed to offer the needed granularity BIB001  Baines and Harisson, 1999;  . The same was observed by BIB002 who could not use SD to model the performance of the individual processes in a software development system". In  ) the authors needed to increase the values of some variables by tenfold in order for SD to "capture" them and for the model to make sense. In addition, while SD permits the study of the stability of the system over the long range, the trends of behaviour that it generates do not indicate what specific actions to be made and at what values of the action parameters. Such specifications require more detailed considerations that SD does not seem to work with, while DES has been effective at.