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Complexity
Volume 2017, Article ID 4791635, 12 pages
https://doi.org/10.1155/2017/4791635
Research Article

Modeling and Simulation of Project Management through the PMBOK® Standard Using Complex Networks

1Department of Information and Computation, Universidad Nacional de Colombia, Sede Manizales, Campus La Nubia, Manizales 170003, Colombia
2Department of Mathematics, Universidad Nacional de Colombia, Sede Manizales, Campus La Nubia, Manizales 170003, Colombia

Correspondence should be addressed to Gerard Olivar-Tost; oc.ude.lanu@travilog

Received 27 August 2017; Accepted 12 November 2017; Published 4 December 2017

Academic Editor: Dimitri Volchenkov

Copyright © 2017 Luz Stella Cardona-Meza and Gerard Olivar-Tost. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Discussion about project management, in both the academic literature and industry, is predominantly based on theories of control, many of which have been developed since the 1950s. However, issues arise when these ideas are applied unilaterally to all types of projects and in all contexts. In complex environments, management problems arise from assuming that results, predicted at the start of a project, can be sufficiently described and delivered as planned. Thus, once a project reaches a critical size, a calendar, and a certain level of ambiguity and interconnection, the analysis centered on control does not function adequately. Projects that involve complex situations can be described as adaptive complex systems, consistent in multiple interdependent dynamic components, multiple feedback processes, nonlinear relations, and management of hard data (process dynamics) and soft data (executive team dynamics). In this study, through a complex network, the dynamic structure of a project and its trajectories are simulated using inference processes. Finally, some numerical simulations are described, leading to a decision making tool that identifies critical processes, thereby obtaining better performance outcomes of projects.