dc.creator | Rodríguez, Daniel | es |
dc.creator | Ruiz Carreira, Mercedes | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.creator | Harrison, Rachel | es |
dc.date.accessioned | 2016-06-16T08:50:22Z | |
dc.date.available | 2016-06-16T08:50:22Z | |
dc.date.issued | 2011 | |
dc.identifier.isbn | 978-1-4503-0557-0 | es |
dc.identifier.uri | http://hdl.handle.net/11441/42380 | |
dc.description.abstract | Traditionally, simulation has been used by project managers
in optimising decision making. However, current simulation
packages only include simulation optimisation which considers
a single objective (or multiple objectives combined
into a single fitness function). This paper aims to describe
an approach that consists of using multiobjective optimisation
techniques via simulation in order to help software
project managers find the best values for initial team size
and schedule estimates for a given project so that cost, time
and productivity are optimised. Using a System Dynamics
(SD) simulation model of a software project, the sensitivity
of the output variables regarding productivity, cost and
schedule using different initial team size and schedule estimations
is determined. The generated data is combined
with a well-known multiobjective optimisation algorithm,
NSGA-II, to find optimal solutions for the output variables.
The NSGA-II algorithm was able to quickly converge to a
set of optimal solutions composed of multiple and conflicting
variables from a medium size software project simulation
model. Multiobjective optimisation and SD simulation
modeling are complementary techniques that can generate
the Pareto front needed by project managers for decision
making. Furthermore, visual representations of such solutions
are intuitive and can help project managers in their
decision making process. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2007-67843-C06-04 | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2010-20057-C03- 03 | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2011-68084-C02-00 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | ACM | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Software Project Management | es |
dc.subject | Simulation Optimisation | es |
dc.subject | Multiobjective Genetic Algorithms | es |
dc.subject | NSGA-II | es |
dc.title | Multiobjective Simulation Optimisation in Software Project Management | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2007-67843-C06-04 | es |
dc.relation.projectID | TIN2010-20057-C03- 03 | es |
dc.relation.projectID | TIN2011-68084-C02-00 | es |
dc.identifier.doi | http://dx.doi.org/10.1145/2001576.2001829 | es |
idus.format.extent | 8 | es |
dc.publication.initialPage | 1883 | es |
dc.publication.endPage | 1890 | es |
dc.eventtitle | 13th annual conference on Genetic and evolutionary computation: GECCO '11 | es |
dc.eventinstitution | Dublin, Ireland | es |
dc.relation.publicationplace | New York | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/42380 | |