Optimization Method of Project Manager Based on Particle Swarm Optimization Algorithm

Yunfen Zang, Xiuting Xu

2022

Abstract

Managers are the guarantee of the project. They are good at execution, leadership and management. A good team of managers can greatly improve the efficiency. However, a good team does not mean that a lot of managers are included. On the contrary, too much managers and an unreasonable distribution would led to many problems such as more project costs and overlapping management functions. In existing research, the management structure and personnel allocation only stay in qualitative analysis. No quantitative indicators have been formed, so that the suggestions given can only give optimization directions and it is difficult to give quantitative goals. A novel project manager optimization method based on particle swarm optimization is proposed. Firstly, a manager optimization model, a project exception handling time model and a cost model respectively are established. And then, the number of managers and Job configuration are optimized with the goal of ensuring timely handling of project exceptions and reducing management costs. Finally, a project with four tasks are used as the research object, and the algorithm convergence speed, task cost and number of managers are studied. The results show that the method can consider the working efficiency of managers and management cost comprehensively. With this method, an optimal management combination can be sought.

Paper Citation

in Harvard Style

Zang Y. and Xu X. (2022). Optimization Method of Project Manager Based on Particle Swarm Optimization Algorithm. In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA; ISBN 978-989-758-658-3, SciTePress, pages 267-273. DOI: 10.5220/0012073100003624

in Bibtex Style

@conference{pmbda22,
author={Yunfen Zang and Xiuting Xu},
title={Optimization Method of Project Manager Based on Particle Swarm Optimization Algorithm},
booktitle={Proceedings of the 2nd International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA},
year={2022},
pages={267-273},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012073100003624},
isbn={978-989-758-658-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA
TI - Optimization Method of Project Manager Based on Particle Swarm Optimization Algorithm
SN - 978-989-758-658-3
AU - Zang Y.
AU - Xu X.
PY - 2022
SP - 267
EP - 273
DO - 10.5220/0012073100003624
PB - SciTePress