159,419 research outputs found
Evaluation of ammunition and fuel supply systems of a Turkish armored battalion during mobilization and deployment using simulation
Cataloged from PDF version of article.In current wars, supply systems have become vital factors to reach military
success. With improvements in technology, the capabilities and means of military units
have also improved and as a result, the supply materials which military units require
have also increased greatly. The timely delivery of supply materials to the combatant
units is the key to success. The delivery of supply materials to combatant units at the
right time and as needed can only be possible with the efficient planning of supply
systems by staff officers. The insufficient evaluation of supply systems will cause
interruptions in delivery of supply materials to combatant units and consequently prevent
the combatant units from accomplishing their tasks.
In this study, the existing ammunition and fuel supply systems of an armored
battalion before alarm order is evaluated via simulation. By using the simulation models
which were coded for existing systems, commanders will have the capability to detect
potential problems and take precautions. The main objectives of this study are: (1) To
evaluate existing systems via simulation because of difficulties in executing real world
systems due to impediments in creating real world conditions and also economic reasons.
(2) To detect the factors which have significant effects on the existing system. (3) To
foresee the probable problems of the existing system by studying the simulation model
outputs using statistical methods. (4) To select the most critical region of Turkey
according to performance measures of interest. The codes of models are created by using
ARENA 3.0 simulation program and SIMAN programming language.Ăzçevik, AydınM.S
The integrated use of enterprise and system dynamics modelling techniques in support of business decisions
Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite
bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use
of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are
then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink
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Decision support for build-to-order supply chain management through multiobjective optimization
This paper aims to identify the gaps in decision-making support based on
multiobjective optimization for build-to-order supply chain management (BTOSCM).
To this end, it reviews the literature available on modelling build-to-order
supply chains (BTO-SC) with the focus on adopting multiobjective optimization
(MOO) techniques as a decision support tool. The literature has been classified based
on the nature of the decisions in different part of the supply chain, and the key
decision areas across a typical BTO-SC are discussed in detail. Available software
packages suitable for supporting decision making in BTO supply chains are also
identified and their related solutions are outlined. The gap between the modelling and
optimization techniques developed in the literature and the decision support needed in
practice are highlighted and future research directions to better exploit the decision
support capabilities of MOO are proposed
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Decision support for build-to-order supply chain management through multiobjective optimization
This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF
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Comparing conventional and distributed approaches to simulation in complex supply-chain health systems
Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with today's powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a 'conventional' approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations
Continuum Modeling and Simulation in Bone Tissue Engineering
Bone tissue engineering is currently a mature methodology from a research perspective.
Moreover, modeling and simulation of involved processes and phenomena in BTE have been proved
in a number of papers to be an excellent assessment tool in the stages of design and proof of concept
through in-vivo or in-vitro experimentation. In this paper, a review of the most relevant contributions
in modeling and simulation, in silico, in BTE applications is conducted. The most popular in silico
simulations in BTE are classified into: (i) Mechanics modeling and sca old design, (ii) transport and
flow modeling, and (iii) modeling of physical phenomena. The paper is restricted to the review of the
numerical implementation and simulation of continuum theories applied to di erent processes in
BTE, such that molecular dynamics or discrete approaches are out of the scope of the paper. Two main
conclusions are drawn at the end of the paper: First, the great potential and advantages that in silico
simulation o ers in BTE, and second, the need for interdisciplinary collaboration to further validate
numerical models developed in BTE.Ministerio de EconomĂa y Competitividad del Gobierno España DPI2017-82501-
Modelling drug coatings: A parallel cellular automata model of ethylcellulose-coated microspheres
Pharmaceutical companies today face a growing demand for more complex drug designs. In the past few decades, a number of probabilistic models have been developed, with the aim of improving insight on microscopic features of these complex designs. Of particular interest are models of controlled release systems, which can provide tools to study targeted dose delivery. Controlled release is achieved by using polymers with different dissolution characteristics. We present here an approach for parallelising a large-scale model of a drug delivery system based on Monte Carlo methods, as a framework for Cellular Automata mobility. The model simulates drug release in the gastro-intestinal tract, from coated ethylcellulose microspheres. The objective is high performance simulation of coated drugs for targeted delivery. The overall aim is to understand the importance of various molecular effects with respect to system evolution over time. Important underlying mechanisms of the process, such as erosion and diffusion, are described
3D multi-agent models for protein release from PLGA spherical particles with complex inner morphologies
In order to better understand and predict the release of proteins from bioerodible micro- or nanospheres, it is important to know the influences of different initial factors on the release mechanisms. Often though it is difficult to assess what exactly is at the origin of a certain dissolution profile. We propose here a new class of fine-grained multi-agent models built to incorporate
increasing complexity, permitting the exploration of the role of different parameters, especially that of the internal morphology of the spheres, in the exhibited release profile. This approach, based on Monte-Carlo (MC) and Cellular Automata (CA) techniques, has permitted the testing of various assumptions and hypotheses about several experimental systems of nanospheres encapsulating proteins. Results have confirmed that this modelling approach
has increased the resolution over the complexity involved, opening promising perspectives for future developments, especially complementing in vitro experimentation
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