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2015 | OriginalPaper | Buchkapitel

Scheduling Projects by a Hybrid Evolutionary Algorithm with Self-Adaptive Processes

verfasst von : Virginia Yannibelli, Analía Amandi

Erschienen in: Advances in Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

In this paper, we present a hybrid evolutionary algorithm with self-adaptive processes to solve a known project scheduling problem. This problem takes into consideration an optimization objective priority for project managers: to maximize the effectiveness of the sets of human resources assigned to the project activities. The hybrid evolutionary algorithm integrates self-adaptive processes with the aim of enhancing the evolutionary search. The behavior of these processes is self-adaptive according to the state of the evolutionary search. The performance of the hybrid evolutionary algorithm is evaluated on six different instance sets and then is compared with that of the best algorithm previously proposed in the literature for the addressed problem. The obtained results show that the hybrid evolutionary algorithm considerably outperforms the previous algorithm.

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Vorheriges Kapitel On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure

Nächstes Kapitel E-HIPS: An Extention of the Framework HIPS for Stagger of Distributed Process in Production Systems Based on Multiagent Systems and Memetic Algorithms

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Titel: Scheduling Projects by a Hybrid Evolutionary Algorithm with Self-Adaptive Processes
verfasst von: Virginia Yannibelli
Analía Amandi
Verlag: Springer International Publishing
Buch: Advances in Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-27059-3

Electronic ISBN: 978-3-319-27060-9

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-27060-9_33

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