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 Innovación TIN2009-1371

Crew Rostering for the High Speed Train

At the time of writing we entered the final stage of implementing the crew rostering system Harmony CDR to facilitate the planning of catering crews on board of the Thalys, the High Speed Train connecting Paris, Cologne, Brussels, Amsterdam, and Geneva. Harmony CDR optimally supports the creation of crew rosters in two ways. Firstly, Harmony CDR contains a powerful algorithm to automatically generate a set of rosters, which is especially developed for this specific situation. As the user has some control over the objectives of the algorithm, several scenarios can be studied before a set of rosters is adopted. An important feature of the automatic roster generator is that it respects requirements, directives, and requests stemming from legal, union, and/or company regulations and/or from individual crew. Secondly, Harmony CDR provides user-interface data manipulation at various levels of detail. The user interface enables the planner to easily obtain many different views on the planning data and to manipulate the planning manually. So again, the planner gets optimal support from the system while he or she is still in control. Also, violating a requirement, directive, or request is detected and displayed, but can be accepted by the planner. In this paper we describe the crew rostering problem for the catering crews of the High Speed Train and the Harmony CDR solution in more detail.decision support systems;railways;crew rostering

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

Crew Scheduling for Netherlands Railways: "destination: customer"

: In this paper we describe the use of a set covering model with additional constraints for scheduling train drivers and conductors for the Dutch railway operator NS Reizigers. The schedules were generated according to new rules originating from the project "Destination: Customer" ("Bestemming: Klant" in Dutch). This project is carried out by NS Reizigers in order to increase the quality and the punctuality of its train services. With respect to the scheduling of drivers and conductors, this project involves the generation of efficient and acceptable duties with a high robustness against the transfer of delays of trains. A key issue for the acceptability of the duties is the included amount of variation per duty. The applied set covering model is solved by dynamic column generation techniques, Lagrangean relaxation and powerful heuristics. The model and the solution techniques are part of the TURNI system, which is currently used by NS Reizigers for carrying out several analyses concerning the required capacities of the depots. The latter are strongly influenced by the new rules.crew scheduling;dynamic column generation;lagrange relaxation;railways;set covering model

Planning and Scheduling of Business Processes in Run-Time: A Repair Planning Example

Over the last decade, the efficient and flexible management of business processes has become one of the most critical success aspects. Furthermore, there exists a growing interest in the application of Artificial Intelligence Planning and Scheduling techniques to automate the production and execution of models of organization. However, from our point of view, several connections between both disciplines remains to be exploited. The current work presents a proposal for modelling and enacting business processes that involve the selection and order of the activities to be executed (planning), besides the resource allocation (scheduling), considering the optimization of several functions and the reach of some objectives. The main novelty is that all decisions (even the activities selection) are taken in run-time considering the actual parameters of the execution, so the business process is managed in an efficient and flexible way. As an example, a complex and representative problem, the repair planning problem, is managed through the proposed approach.Ministerio de Ciencia e Innovación TIN2009-13714Junta de Andalucía P08-TIC-0409

OptEEmAL: Decision-Support Tool for the Design of Energy Retrofitting Projects at District Level

Designing energy retrofitting actions poses an elevated number of problems, as the definition of the baseline, selection of indicators to measure performance, modelling, setting objectives, etc. This is time-consuming and it can result in a number of inaccuracies, leading to inadequate decisions. While these problems are present at building level, they are multiplied at district level, where there are complex interactions to analyse, simulate and improve. OptEEmAL proposes a solution as a decision-support tool for the design of energy retrofitting projects at district level. Based on specific input data (IFC(s), CityGML, etc.), the platform will automatically simulate the baseline scenario and launch an optimisation process where a series of Energy Conservation Measures (ECMs) will be applied to this scenario. Its performance will be evaluated through a holistic set of indicators to obtain the best combination of ECMs that complies with user's objectives. A great reduction in time and higher accuracy in the models are experienced, since they are automatically created and checked. A subjective problem is transformed into a mathematical problem; it simplifies it and ensures a more robust decision-making. This paper will present a case where the platform has been tested.This research work has been partially funded by the European Commission though the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 680676. All related information to the project is available at https://www.opteemal-project.eu