A multi-modal discrete-event simulation model for military deployment

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Ph.D.) -- Bilkent University, 2009.Includes bibliographical references leaves 132-136.This study introduces a logistics and transportation simulation as a tool that can be used to provide insights into potential outcomes of proposed military deployment plans.    More specifically, we model a large‐scale real‐world military Deployment Planning Problem (DPP) that involves planning the movement of military units from their home bases to their final destinations using different transportation assets on a multimodal transportation network.    We apply, for the first time, the Event Graph methodology and Listener Event Graph Object framework to create a discrete event simulation (DES) model of the DPP.  We use and extend Simkit, an open‐source Java Application Programming Interface for creating DES models.    The high‐resolution approach that we take in most part, allows us to estimate whether a given plan of deployment will go as intended, and determine prospective problem areas in a relatively short time compared to other existing simulations because of the absence of the need to use several models of differing resolutions in succession as often done in literature.  For a typical deployment scenario for four battalions, run times are between 25 to 27 minutes for 60 runs of the model on a 1.6 GHz Pentium(R) M PC with 512 MB RAM.  That is less than 30 seconds per run.      To accurately incorporate real and detailed transportation network data into the simulation, we use GeoKIT, a state‐of‐the‐art, Java‐based Geographical Information System.    The component‐based approach adopted in development of our simulation model enables us to easily integrate future additions to our model.  The DES developed as part of this dissertation provides a test bed for currently existing deployment scenarios.    While our DES model is not a panacea for all, it allows for testing the feasibility and sensitivity of deployment plans under stochastic conditions prior to committing members of the military into harm’s way.    Our main contribution is to develop a comprehensive, multi‐modal, high‐ resolution, loosely‐coupled and modular, extendable, platform independent, state‐of‐ the‐art GIS based simulation environment that views the deployment operations as end‐to‐end processes.    Such a simulation environment for multi modal deployment planning and analysis does not exist.       Additionally, we simulate and analyze a typical real‐world case study by using conventional methods and the rather novice Nearly Orthogonal Latin Hypercube Sampling (NOLHS) technique.  We use a space‐filling nearly orthogonal design of 29 factors and 257 runs to determine the factors that impact most on a deployment plan.  We make 15 replications of each of the 257 runs (scenarios) to reach a total of 257x15=3855 computer runs compared to an experiment with 29 factors, each with only 2 levels and 15 replications per run, for a complete enumeration experiment (229 x15= 8,053,063,680 computer runs!).   Yıldırım, Uğur ZiyaPh.D

Modular development of manufacturing simulation models.

It is common practice within manufacturing companies to create simulation models at different time periods. These models are often used to represent various parts of the manufacturing systems. In general, these pre-built simulation models are required to be integrated together in order to evaluate the entire manufacturing system, this is not a simple task. This research addresses the issues involved in the integration of pre-built simulation models. An in depth literature review was carried out to identify current strategies to overcome these issues. Based on structured research work, a set of recommendations is proposed to ensure easy integration of models. This set of recommendations will help simulation practitioners to minimise the errors occurred during the integration of simulation models. The findings conclude more effort is required than is anticipated by most model builders and involves far more than 'just simply changing' the name of variables. A set of recommendations is therefore proposed to cope with the complexity and understanding of manufacturing systems. The research focuses on manufacturing systems but in general can be applied elsewhere

Modular development of manufacturing simulation models.

It is common practice within manufacturing companies to create simulation models at different time periods. These models are often used to represent various parts of the manufacturing systems. In general, these pre-built simulation models are required to be integrated together in order to evaluate the entire manufacturing system, this is not a simple task. This research addresses the issues involved in the integration of pre-built simulation models. An in depth literature review was carried out to identify current strategies to overcome these issues. Based on structured research work, a set of recommendations is proposed to ensure easy integration of models. This set of recommendations will help simulation practitioners to minimise the errors occurred during the integration of simulation models. The findings conclude more effort is required than is anticipated by most model builders and involves far more than 'just simply changing' the name of variables. A set of recommendations is therefore proposed to cope with the complexity and understanding of manufacturing systems. The research focuses on manufacturing systems but in general can be applied elsewhere

Modular development of manufacturing simulation models.

It is common practice within manufacturing companies to create simulation models at different time periods. These models are often used to represent various parts of the manufacturing systems. In general, these pre-built simulation models are required to be integrated together in order to evaluate the entire manufacturing system, this is not a simple task. This research addresses the issues involved in the integration of pre-built simulation models. An in depth literature review was carried out to identify current strategies to overcome these issues. Based on structured research work, a set of recommendations is proposed to ensure easy integration of models. This set of recommendations will help simulation practitioners to minimise the errors occurred during the integration of simulation models. The findings conclude more effort is required than is anticipated by most model builders and involves far more than 'just simply changing' the name of variables. A set of recommendations is therefore proposed to cope with the complexity and understanding of manufacturing systems. The research focuses on manufacturing systems but in general can be applied elsewhere

Quality of service in optical burst switching networks

Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2009Fundação para e Ciência e a Tecnologi

Methodology to develop hybrid simulation/emulation model.

Trends towards reduced life-time of products and globalised competition has increased pressure on manufacturing industries to be more responsive to changing needs of product markets. Consequently, the use of simulation to describe short term future performance of manufacturing system has become more significant than ever. An application of simulation that has attracted attention is for testing of control logic before commissioning on site by using a detailed simulation model called emulation model. However, though the success of using emulation particularly in improving cost-effectiveness of automated material handling system delivery has been acknowledged by industries and simulation model developers, the uptake for this technology is still low. The major inhibitors are the high costs of its model building as well as simulation and emulation models are perceived to be non convertible.The main objective, of this research is to establish a methodology to develop simulation model that can be converted into emulation model with ease, thus making emulation technology more affordable. The product of this research called the methodology to build Hybrid Simulation Emulation Model (HSEM) is a new approach of building emulation model comprising of three phases namely (1) development of base simulation model, (2) development of detail emulation model, and (3) integration of controller with the emulation model. Important requirements for HSEM are flexibility of adding details to the simulation model and inter process communication between model and real control system. To facilitate implementation of the methodology, it is essential that the simulation software package provide functionalities for modular model development, access and adding of codes, integration with other application and real time (RT) modelling.The methodology developed offers a more affordable emulation modelling and an opening for further research into the comprehensive support for the implementation of real time control system testing using emulation