Web Application for Hierarchical Organizational Structure Optimization – Human Resource Management Case Study

计算机科学 有限状态机 自动机 JavaScript 遗传算法 层级组织 分层数据库模型 理论计算机科学 流量(数学) 数学优化 数据挖掘 算法 机器学习 数学 程序设计语言 管理 经济 几何学
作者
Davorin Kofjač,Blaž Bavec,Andrej Škraba
出处
期刊:Organizacija [De Gruyter Open]
卷期号:48 (3): 177-186 被引量:2
标识
DOI:10.1515/orga-2015-0012
摘要

Abstract Background and Purpose: In a complex strictly hierarchical organizational structure, undesired oscillations may occur, which have not yet been adequately addressed. Therefore, parameter values, which define fluctuations and transitions from one state to another, need to be optimized to prevent oscillations and to keep parameter values between lower and upper bounds. The objective was to develop a simulation model of hierarchical organizational structure as a web application to help in solving the aforementioned problem. Design/Methodology/Approach: The hierarchical structure was modeled according to the principles of System Dynamics. The problem of the undesired oscillatory behavior was addressed with deterministic finite automata, while the flow parameter values were optimized with genetic algorithms. These principles were implemented as a web application with JavaScript/ECMAScript. Results: Genetic algorithms were tested against well-known instances of problems for which the optimal analytical values were found. Deterministic finite automata was verified and validated via a three-state hierarchical organizational model, successfully preventing the oscillatory behavior of the structure. Conclusion: The results indicate that the hierarchical organizational model, genetic algorithms and deterministic finite automata have been successfully implemented with JavaScript as a web application that can be used on mobile devices. The objective of the paper was to optimize the flow parameter values in the hierarchical organizational model with genetic algorithms and finite automata. The web application was successfully used on a three-state hierarchical organizational structure, where the optimal flow parameter values were determined and undesired oscillatory behavior was prevented. Therefore, we have provided a decision support system for determination of quality restructuring strategies.
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