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Genetic algorithm of network graph multi-objective optimization as an instrument of project monitoring

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dc.contributor.author Prokopyev O.
dc.date.accessioned 2018-09-18T20:28:57Z
dc.date.available 2018-09-18T20:28:57Z
dc.date.issued 2015
dc.identifier.issn 1911-2017
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/140352
dc.description.abstract © 2015 Canadian Center of Science and Education. All rights reserved. Proper tracking of progress remains a vital part of modern project management, defining prospects of successful implementation of planned tasks. There are several popular concepts of project monitoring, such as logical framework approach (LFA), earned value management (EVM), etc., and each of them depends on properly optimized network graph that represents dependences between project tasks. Article describes the features and problems of multi-objective optimization in project management with reference to network graphs. The significant role of network graph optimization for project monitoring systems is proved and the model of multi-objective optimization of the network graph on criterion functions of duration and project cost based on NSGA-II genetic algorithm is proposed as the main purpose of research. Model takes into account the reserves of time on a critical way of the network graph, possibility of decreasing the load of available resources at the expense of time reserves on non-critical ways of the network graph, variety of used resources and options of delegation. One of its main advantages is quite low laboriousness of implementation, that depends on number of nodes on the network graph of the project and on number of possible options of delegation for the project tasks with several alternatives of delegation. Model has been tested on sample project with real data and results have been analyzed.
dc.relation.ispartofseries Asian Social Science
dc.subject Genetic algorithms
dc.subject Multi-objective optimization
dc.subject Network graphs
dc.subject Project monitoring
dc.subject Project scheduling
dc.title Genetic algorithm of network graph multi-objective optimization as an instrument of project monitoring
dc.type Article
dc.relation.ispartofseries-issue 1
dc.relation.ispartofseries-volume 11
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 204
dc.source.id SCOPUS19112017-2015-11-1-SID84915791139


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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