Hybrid Discrete Event/Agent Based Model of Career Development.

A. Cherkassky, Eugene Bumagin
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Abstract

This is Part 2 of article dedicated to modeling and simulation of career development processes. The simulation algorithm presented here is built on a combined platform of Discrete Events and Agent Based modeling. Main components of the model are employees/agents, the career history of each of which is reproduced in the model. The model takes into account individual characteristics of the agent, the structure and characteristics of the organization personnel policy and many other random factors inherent in career development processes. The hybrid model consists two main sub-models – the sub-model of the agent flow and the submodel of agents’ interaction, which provides simulation of career development processes. The Part 1 of the article presents the sub-model of the agent flow, which is based on the results of a survey of respondents and on a series of theoretical assumptions that made it possible to construct a Discrete Event model of the agent flow. In this part of the article, we present a detailed algorithm related to the Agent Based submodel of the career development processes. The article addresses the production and career components of the agent activity; two types of career mechanisms – a push and a pull movement; the emergence, development and influence of agent coalitions on career development process; the dynamic processes of the agent activity variation, and a number of other factors affecting the career development process.

The algorithms were implemented in the form of Java code. The program code of the model allows you to track and store the career history of each agent, its interaction with other agents, the effect of the model parameters, and evaluate the contribution of each agent and group of agents to the organization's production achievements.
基于离散事件/智能体的职业发展混合模型。
这是关于职业发展过程建模和仿真的文章的第2部分。本文提出的仿真算法是建立在离散事件和基于Agent的建模相结合的平台上的。模型的主要组成部分是雇员/代理人,每个人的职业历史都在模型中重现。该模型考虑了代理人的个体特征、组织人事政策的结构和特征以及职业发展过程中固有的许多其他随机因素。该混合模型包括两个主要的子模型——代理流子模型和代理交互子模型,提供了职业发展过程的仿真。本文的第1部分介绍了代理流的子模型,该模型基于对受访者的调查结果和一系列理论假设,这些假设使得构建代理流的离散事件模型成为可能。在本文的这一部分,我们提出了一个详细的基于Agent的职业发展过程子模型的算法。本文讨论了代理人活动的生产和职业组成部分;两种职业机制——推式和拉式运动;代理人联盟的产生、发展及其对职业发展过程的影响代理人活动变化的动态过程,以及其他一些影响职业发展过程的因素。算法以Java代码的形式实现。该模型的程序代码允许您跟踪和存储每个agent的职业历史,它与其他agent的交互,模型参数的影响,并评估每个agent和agent组对组织生产成果的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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