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discrete events simulation model  (MathWorks Inc)


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    MathWorks Inc discrete events simulation model
    Discrete Events Simulation Model, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/discrete-event+simulation+model/pm37386254-79-12-21
    Average 90 stars, based on 1 article reviews
    discrete events simulation model - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Circulation network design for urban rail transit station using a PH(n)/PH(n)/C/C queuing network model
    Article Snippet: Width is crucial to the performance of circulation network in urban rail transit station.. However, poor performance has been observed in most existing circulation systems.. In fact, randomness and statedependence exist in circulation network where blocking and feedback cannot be ignored.

    Article Title: Designing resilient military logistics with additive manufacturing
    Article Snippet: Purpose – In this study, the authors explore how novel and relevant technologies can change the overall design of systems, and which factors influence the design of resilient systems in particular.. After evaluating the effects of these factors, the authors describe the potential role of AM-supported maintenance operations in military logistics and draw broader conclusions regarding designing for resilience.. Design/methodology/approach –The authors build a simulation model of the AM-supported maintenance capability of a mechanised battalion to analyse factors affecting its resilience.

    Construct:

    Article Title: An agent-based approach for supply chain retrofitting under uncertainty
    Article Snippet: In this work, decisions that have a long lasting effect on the supply chain (SC) such as the design and retrofit of a production/distribution network re considered.. The retrofitting tasks are accomplished by using a SC agent-oriented simulation system, which model each entity belonging to the C as an independent agent.. The starting point is a set of possible design options for the existing SC.



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    Markov and the <t>Discrete</t> <t>Event</t> <t>Simulation</t> models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted
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    Markov and the Discrete Event Simulation models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted

    Journal: Health Economics Review

    Article Title: Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

    doi: 10.1186/s13561-021-00312-4

    Figure Lengend Snippet: Markov and the Discrete Event Simulation models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted

    Article Snippet: Decision analytic models: a Markov model and a Discrete event simulation model were constructed using TreeAge Pro 2020 with the purpose of estimating the incremental costs and quality-adjusted life years (QALY) (Fig. ).

    Techniques: Transplantation Assay

    Cost (AUD), QALY and net monetary benefit per patient by model and time-horizon for the Markov and DES models

    Journal: Health Economics Review

    Article Title: Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

    doi: 10.1186/s13561-021-00312-4

    Figure Lengend Snippet: Cost (AUD), QALY and net monetary benefit per patient by model and time-horizon for the Markov and DES models

    Article Snippet: Decision analytic models: a Markov model and a Discrete event simulation model were constructed using TreeAge Pro 2020 with the purpose of estimating the incremental costs and quality-adjusted life years (QALY) (Fig. ).

    Techniques: