Flexible Project Scheduling Algorithms

Despite the emerging importance of flexible project management approaches, such as agile extreme and hybrid methodologies, the algorithmic support of these approaches is still insufficient. In addition, single project scheduling has received far more attention than have schedules of multilevel projects, such as project portfolios or multi projects. This lack of scheduling techniques is especially true for flexible portfolios, such as agile, hybrid, and extreme project portfolios. While multilevel project scheduling algorithms already exist for fixed multilevel project structures, they are not able to handle flexible structures. This chapter proposes algorithms to schedule both flexible single and multilevel projects. The proposed algorithms handle both flexible and unplanned tasks and dependencies. They handle both single and multimode completion modes, and both renewable and nonrenewable resources. In addition, this chapter proposes a matrix-based risk-valuation framework to evaluate risk effects for flexible projects and portfolios. With this framework, project scheduling approaches are compared

Serviceability of large-Scale systems

One of the most important research fields of network sciences is the robustness of networks. A recently answered important question was the following: Which network topologies are more resistant to random malfunctions and/or direct attacks? Nevertheless, until now, which system topology can be maintained and how to manage maintenance more efficiently and effectively have been open questions. However, these questions are the keys both to designing large-scale systems and to scheduling maintenance tasks. This paper proposes a new means to analyze the maintainability of a large system by combining two kinds of networks, i.e., the reliability diagram of the system (1) and the network of scheduled maintenance tasks (2). This paper shows how to assign maintenance task(s) to a system component to increase the reliability of the system. With the proposed method, the maintainability of large-scale systems can be analyzed

Developing Expert System for Managing Maintenance Projects

Handling specialities of maintenance projects is a highly challenging task. On the one hand the operations of the maintenance task are fixed, and can be described with a network or process planning methods. On the other hand the sequence of realizing maintenance tasks depend on the risks and reliabilities. Therefore, traditional project and process planning methods are not the most appropriate ones at managing the sequence of maintenance tasks. In this paper a new planning method is introduced, where project constraints can be considered in determining the optimal maintenance project. Tasks which have to be realized can be ranked with our method based on their reliabilities or risks. Estimating reliabilities, theory of stochastic process and expressing of measurement uncertainty are also applied and improved in order to handle decision errors and their consequences. To determine feasible maintenance projects an expert system has been developed to determine which application can be used for diagnostic processes and forecasting the failures

Hybrid time-quality-cost trade-off problems

Agile and hybrid project management has become increasingly popular among practitioners, particularly in the IT sector. In contrast to the theoretically and algorithmically well-established and developed time-cost and time-quality-cost project management methods, agile and hybrid project management lacks a principle foundation and algorithmic treatment. The aim of this paper is to fill this gap. We propose a matrix-based method that provides scores for alternative project plans that host flexible task dependencies and undecided, supplementary task completion while also covering traditional time-quality-cost trade-off problems. The proposed method can bridge the agile and traditional approaches. Keywords: Time-quality-cost trade-off problems, Hybrid project management approaches, Matrix-based project plannin

Investigating Erasmus mobility exchange networks with gravity models

AbstractThe Erasmus mobility exchange program is one of the most considerable cooperation and mobility networks in the world; however, the driving forces of the mobility exchange program are still questionable. Integrating various databases and including new indicators, such as crimes, collaboration, and culture, called the 3Cs in our model, offers us new insights into the driving forces of mobility. In contrast to most studies, this research is based on the entire Erasmus network, which is investigated at both institutional and regional (NUTS3 or county) levels. The advantage of investigating entire mobility networks is that it helps avoid sampling distortions. Nevertheless, the interpretation is more challenging than with other investigation scopes since most identified factors act as indicators rather than proxies of the driving forces of mobility exchanges. Despite this interpretation difficulty, conclusions about the entire network can only be drawn by examining the whole mobility exchange network. In this study, the network of Erasmus student exchange programs between 2008 and 2013 is investigated both overall and separated by subject area. The study identifies the individual, institutional, and county-wide driving forces of mobility. One of the main exciting findings that the applied gravity models suggest is that there are three principal driving forces, national culture, collaboration, and crime dimensions of the host countries, which have not yet been studied in terms of Erasmus exchange networks