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    <title>Auteurs : Miroljub Kljajic</title>
    <link>http://popups.lib.uliege.be/1373-5411/index.php?id=1587</link>
    <description>Publications of Auteurs Miroljub Kljajic</description>
    <language>fr</language>
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      <title>Determination of optimal control strategy in strict hierarchical manpower system</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=4464</link>
      <description>Present paper addresses an approach to determine optimal recruitment and transi tion strategies in strict hierarchical manpower system by the application of simula tion modeling and optimization methods. The transition model is represented in the form of discrete state space. The target values for each particular rank are deter mined by the user defined trajectory function. Optimal recruitment and transition dynamics is determined by the minimization of the differences between desired and actual state values. Analytical approach to the optimization is considered in order to provide proper control strategy. </description>
      <pubDate>Fri, 11 Oct 2024 11:26:13 +0200</pubDate>
      <lastBuildDate>Fri, 11 Oct 2024 11:26:20 +0200</lastBuildDate>
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      <title>Simulation-Based Decision Support Modeling and Validation of Weak Anticipative System</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3926</link>
      <description>Organizational systems are one of the more remarkable classes of weak anticipative systems in which decision making is the main force for its functioning and development. Simulation-based decision support is a holistic methodology for decision assessment in organizations. System dynamics is a proper methodology for modeling and testing the dynamic hypotheses of organizational systems. The role of subjects in model development and its validation from cybernetic, psychological and cognitive perspectives are discussed in this paper. Group participation in model building and validation is suggested in order to prevent the manipulation of dominant subjects and/or implicit dictators during modeling. This paper concludes with some useful examples of systems simulation in solving real problems. </description>
      <pubDate>Tue, 01 Oct 2024 15:27:54 +0200</pubDate>
      <lastBuildDate>Tue, 01 Oct 2024 15:28:13 +0200</lastBuildDate>
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      <title>Anticipation as the Source of Synchronization in Discrete Agents</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3260</link>
      <description>Present paper address the synchronization classification of discrete agents by the means of z-transform. The developed agent based anticipative model enables us to change the future as well as the past chain of events. Emergent synchronization patterns determined by the application of z-transform provide the base for determination of stability regions in systems of higher complexities. One of the important results provided is that the proposed agent-based system is apparently controllable by considering the frequency response of the system. The proof of the stability for the arbitrary set of proposed anticipatory agents is proposed. </description>
      <pubDate>Fri, 13 Sep 2024 13:34:46 +0200</pubDate>
      <lastBuildDate>Tue, 08 Oct 2024 17:24:00 +0200</lastBuildDate>
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      <title>Group Learning Supported by a Simulation Model – An Experiment Design</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3254</link>
      <description>This paper addresses the influence of information feedback on a decision process supported by a simulation model. A group of 118 graduate students participated in the experiment under four conditions : a1) decision making with application of the simulation model with pretest, a2) decision making with application of the simulation model and group information feedback with pretest, a3) decision making with application of the simulation model without pretest, and a4) decision making with application of the simulation model and group information feedback without pretest. The criteria function and number of simulation runs were observed. The hypothesis that decision-making using a simulation model and group feedback improve criteria function was confirmed. The model of learning during the decision process was developed. </description>
      <pubDate>Fri, 13 Sep 2024 13:26:30 +0200</pubDate>
      <lastBuildDate>Thu, 10 Oct 2024 10:39:49 +0200</lastBuildDate>
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      <title>Simulation Approach to Decision Support in Complex System</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=1582</link>
      <description>In the paper, the simulation approach to decision support in enterprise has been described. The role of the subject in the modelling of a complex system is discussed. It shows that the main problem in the modelling of complex systems derives from the complexity of the systems themselves and not from the short comings of the particular methodology. The article continues with the general simulation model of the business system described by Forrester's system dynamics. The methodology is sufficiently abstact to allow a qualitative and quantitative analysis of system functioning through feedback loops. The multiple criteria function used for the evaluation of different scenarios was defined with the aid of a decision group using the group support system. The methodology was successfully tested on real cases. </description>
      <pubDate>Mon, 15 Jul 2024 15:15:01 +0200</pubDate>
      <lastBuildDate>Mon, 07 Oct 2024 12:42:56 +0200</lastBuildDate>
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