NDLI: On the scalability of multi-objective metaheuristics for the software scheduling problem

Content Provider	IEEE Xplore Digital Library
Author	Luna, F. Gonzalez-Alvarez, D.L. Chicano, F. Vega-Rodriguez, M.A.
Copyright Year	2011
Description	Author affiliation: University of Málaga, Málaga, Spain (Luna, F.; Chicano, F.) \|\| University of Extremadura, Cáceres, Spain (Gonzalez-Alvarez, D.L.; Vega-Rodriguez, M.A.)
Abstract	The Software Project Scheduling (SPS) problem relates to the decision of who does what during a software project lifetime. This problem has a capital importance for software companies, where the total budget and human resources involved in software development must be managed optimally in order to end up with a successful project. Companies are mainly concerned with reducing both the duration and the cost of the projects, and these two goals are in conflict with each other. A multi-objective approach is therefore the natural way of facing the SPS problem and multi-objective metaheuristics have been used to solve the problem in the past. Nowadays, software projects faced by the large companies are increasing in size and we need algorithms that are able to deal with the new large instances of the SPS problem. In this paper we analyze the scalability of four multi-objective algorithms when they are applied to the SPS problem using instances of increasing size. The algorithms are a genetic algorithm (NSGA-II), an evolution strategy (PAES), a differential evolution (DEPT) and a firefly algorithm (MO-FA). The results suggest that PAES is the algorithm with the best scalability behaviour.
Starting Page	1110
Ending Page	1115
File Size	282257
Page Count	6
File Format	PDF
ISBN	9781457716768
ISSN	21647151
e-ISBN	9781457716768
DOI	10.1109/ISDA.2011.6121807
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-22
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Scalability Software algorithms Software project scheduling scalability analysis Maintenance engineering Approximation algorithms Software multi-objective optimization Approximation methods
Content Type	Text
Resource Type	Article

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