Innovative Approach in Modeling Business Processes with a Focus on Improving the Allocation of Human Resources
Almir Djedovic,
Almir Karabegovic,
Zikrija Avdagic and
Samir Omanovic
Mathematical Problems in Engineering, 2018, vol. 2018, 1-14
Abstract:
Organizations can improve efficiency of process execution through a correct resource allocation, as well as increase income, improve client satisfaction, and so on. This work presents a novel approach for solving problems of resource allocation in business processes which combines process mining, statistical techniques, and metaheuristic algorithms for optimization. In order to get more reliable results of the simulation, in this paper, we use process mining analysis and statistical techniques for building a simulation model. For finding optimal human resource allocation in business processes, we use the improved differential evolution algorithm with population adaptation. Because of the use of a stochastic simulation model, noise appears in the output of the model. The differential evolution algorithm is modified in order to include uncertainty in the fitness function. In the end, validation of the model was done on three different data sets in order to demonstrate the generality of the approach, and the comparison with the standard approach from the literature was done. The results have shown that this novel approach gives solutions which are better than the existing model from literature.
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2018/9838560.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2018/9838560.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9838560
DOI: 10.1155/2018/9838560
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().