77,785 research outputs found
Business Process Instances Scheduling with Human Resources Based on Event Priority Determination
International audienceBusiness Process Management (BPM) is concerned with continuously enhancing business processes. However, this cannot be achieved without an effective Resource allocation and a priority-based scheduling. These are important steps towards time, cost and performance optimization in business processes. Even though there are several approaches and algorithms for scheduling and resource allocation problems, they do not take into consideration information gathered from past process executions, given the stateless aspect of business processes. Extracting useful knowledge from this information can help achieving an effective instance scheduling decisions without compromising cost or quality of service. In this paper, we pave the way for a combination approach which is based on unsupervised machine learning algorithms for clustering and genetic algorithm (GA) to ensure the assignment of the most critical business process instance tasks, to the qualified human resource while respecting several constraints such as resource availability and reliability, and taking into consideration the priority of the events that launch the process instances. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions
Welcome to OR&S! Where students, academics and professionals come together
In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities
An Automatic and Intelligent System for Integrated Healthcare Processes Management
In this work, an automatic and intelligent system for integrated healthcare processes
management is developed on a constraint based system. This project has been carried out in
collaboration with a real assisted repro-duction clinic. Our goal is to improve the efficiency of the
clinic by facilitating the management of the integrated healthcare system. This is very important
in an environment in which the healthcare processes present complex temporal and resource
constraints.Ministerio de EconomĂa y Competitividad TIN2016-76956-C3-2-RMinisterio de EconomĂa y Competitividad TIN2015-71938-RED
Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud
With the advent of cloud computing, organizations are nowadays able to react
rapidly to changing demands for computational resources. Not only individual
applications can be hosted on virtual cloud infrastructures, but also complete
business processes. This allows the realization of so-called elastic processes,
i.e., processes which are carried out using elastic cloud resources. Despite
the manifold benefits of elastic processes, there is still a lack of solutions
supporting them.
In this paper, we identify the state of the art of elastic Business Process
Management with a focus on infrastructural challenges. We conceptualize an
architecture for an elastic Business Process Management System and discuss
existing work on scheduling, resource allocation, monitoring, decentralized
coordination, and state management for elastic processes. Furthermore, we
present two representative elastic Business Process Management Systems which
are intended to counter these challenges. Based on our findings, we identify
open issues and outline possible research directions for the realization of
elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and
P. Hoenisch (2015). Elastic Business Process Management: State of the Art and
Open Challenges for BPM in the Cloud. Future Generation Computer Systems,
Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
On the use of empirical or artifical project data
This paper gives a brief overview of the artificial and empirical project data generated and collected by the researchers from the Operations Research and Scheduling (OR&S) group from Ghent University in Belgium. Artificial data are generated by project network generators under a strict design to control both the network structure and the resource constraints, while the empirical project data are collected over a time horizon of multiple years, using a standardized collection and classification method. All data are publicly available on the OR&S website www.projectmanagement.ugent.
be/research/data) and can be used anywhere for academic purposes. More
detailed information on the network and resource parameters used to
generate the artificial data and the classification process for the collection
of empirical data is available in a paper published in the Journal of Modern
Project Management (Vanhoucke et al., 2016)
Optimized Time Management for Declarative Workflows
Declarative process models are increasingly used since they fit better
with the nature of flexible process-aware information systems and the requirements
of the stakeholders involved. When managing business processes, in addition,
support for representing time and reasoning about it becomes crucial. Given
a declarative process model, users may choose among different ways to execute
it, i.e., there exist numerous possible enactment plans, each one presenting specific
values for the given objective functions (e.g., overall completion time). This
paper suggests a method for generating optimized enactment plans (e.g., plans
minimizing overall completion time) from declarative process models with explicit
temporal constraints. The latter covers a number of well-known workflow
time patterns. The generated plans can be used for different purposes like providing
personal schedules to users, facilitating early detection of critical situations,
or predicting execution times for process activities. The proposed approach is
applied to a range of test models of varying complexity. Although the optimization
of process execution is a highly constrained problem, results indicate that
our approach produces a satisfactory number of suitable solutions, i.e., solutions
optimal in many cases
OptBPPlanner: Automatic Generation of Optimized Business Process Enactment Plans
Unlike imperative models, the specifi cation of business process (BP)
properties in a declarative way allows the user to specify what has to be done instead
of having to specify how it has to be done, thereby facilitating the human work
involved, avoiding failures, and obtaining a better optimization. Frequently, there
are several enactment plans related to a specifi c declarative model, each one
presenting specifi c values for different objective functions, e.g., overall completion
time. As a major contribution of this work, we propose a method for the automatic
generation of optimized BP enactment plans from declarative specifi cations. The
proposed method is based on a constraint-based approach for planning and scheduling
the BP activities. These optimized plans can then be used for different purposes
like simulation, time prediction, recommendations, and generation of optimized BP
models. Moreover, a tool-supported method, called OptBPPlanner, has been implemented
to demonstrate the feasibility of our approach. Furthermore, the proposed
method is validated through a range of test models of varying complexity.Ministerio de Ciencia e InnovaciĂłn TIN2009-1371
A survey of variants and extensions of the resource-constrained project scheduling problem
The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts. --project scheduling,modeling,resource constraints,temporal constraints,networks
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