Multi Project Organization Optimization using Genetic Algorithm

Sven Tackenberg, Sebastian Schneider

Abstract

Due to impatient customers and competitive threats, it has become increasingly important to shorten the lead time of development projects and to bring new products faster to the market. Furthermore, many organizations are faced with the challenge of planning and managing the simultaneous execution of multiple dependent projects under tight time and resource constraints. Within that kind of business environment, effective project management and scheduling is crucial to organizational performance. A genetic algorithm approach with a novel genotype and GP mapping operation is proposed to minimize the overall project duration and budget of multiple projects for a resource constrained multi project scheduling problem (RCMPSP) without violating inter-project resource constraints or intra-project precedence constraints. Stochastic rework of tasks, variable assignment of actors and stochastic makespan of a specific task are considered by the introduced GA. The proposed Genetic Algorithm is tested on scheduling problems with and without stochastic feedback. This GA demonstrates to provide a quick convergence to a global optimal solution regarding the multi-criteria objectives.

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Paper Citation


in Harvard Style

Tackenberg S. and Schneider S. (2009). Multi Project Organization Optimization using Genetic Algorithm . In Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009) ISBN 978-989-8111-90-6, pages 101-115. DOI: 10.5220/0002219801010115


in Bibtex Style

@conference{msvveis09,
author={Sven Tackenberg and Sebastian Schneider},
title={Multi Project Organization Optimization using Genetic Algorithm},
booktitle={Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009)},
year={2009},
pages={101-115},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002219801010115},
isbn={978-989-8111-90-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009)
TI - Multi Project Organization Optimization using Genetic Algorithm
SN - 978-989-8111-90-6
AU - Tackenberg S.
AU - Schneider S.
PY - 2009
SP - 101
EP - 115
DO - 10.5220/0002219801010115