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

Automatic generation of optimized business process models from constraint-based specifications

Business process (BP) models are usually defined manually by business analysts through imperative languages considering activity properties, constraints imposed on the relations between the activities as well as different performance objectives. Furthermore, allocating resources is an additional challenge since scheduling may significantly impact BP performance. Therefore, the manual specification of BP models can be very complex and time-consuming, potentially leading to non-optimized models or even errors. To overcome these problems, this work proposes the automatic generation of imperative optimized BP models from declarative specifications. The static part of these declarative specifications (i.e. control-flow and resource constraints) is expected to be useful on a long-term basis. This static part is complemented with information that is less stable and which is potentially unknown until starting the BP execution, i.e. estimates related to (1) number of process instances which are being executed within a particular timeframe, (2) activity durations, and (3) resource availabilities. Unlike conventional proposals, an imperative BP model optimizing a set of instances is created and deployed on a short-term basis. To provide for run-time flexibility the proposed approach additionally allows decisions to be deferred to run-time by using complex late-planning activities, and the imperative BP model to be dynamically adapted during run-time using replanning. To validate the proposed approach, different performance measures for a set of test models of varying complexity are analyzed. The results indicate that, despite the NP-hard complexity of the problems, a satisfactory number of suitable solutions can be produced.Ministerio de Ciencia e Innovación TIN2009-1371

User recommendations for the optimized execution of business processes

In order to be able to flexibly adjust a company's business processes (BPs) there is an increasing interest in flexible process-aware information systems (PAISs). This increasing flexibility, however, typically implies decreased user guidance by the PAIS and thus poses significant challenges to its users. As a major contribution of this work, we propose a recommendation system which assists users during process execution to optimize performance goals of the processes. The recommendation system is based on a constraint-based approach for planning and scheduling the BP activities and considers both the control-flow and the resource perspective. To evaluate the proposed constraint-based approach different algorithms are applied to a range of test models of varying complexity. The results indicate that, although the optimization of process execution is a highly constrained problem, the proposed approach produces a satisfactory number of suitable solutions.Ministerio de Ciencia e Innovación TIN2009-1371

Automatic Generation of Questionnaires for Managing Configurable BP Models

Managing large collections of business process (BP) models is increasingly being necessary for organizations. For this, configurable BP models can be used for managing these BPs while allowing analysts to understand what these BPs share and what their differences are. Before the execution of the configurable BP model, a BP model has to be selected from it. This selection is typically performed by an analyst who manually individualizes the model in order to address the business requirements. Unlike existing approaches, we propose a totally automated method to create a questionnaire-based application for guiding a business expert on individualizing a model

Generating Multi-objective Optimized Configurable Business Process Models

The manual specification of imperative business process (BP) models can be very complex and time-consuming, potentially leading to non-optimized models or even errors. To support process analysts in the definition of these models, a method for generating optimized configurable BP models from a constraint-based specification by considering multiple objectives is described. A constraint-based specification typically allows for several different ways of executing it leading to several enactment plans which can, however, vary greatly in respect to how well different performance objective functions can be achieved.We therefore automatically generate different plans and select the ones which fit best the objectives of the company. The generated plans are then merged into an optimized configurable BP model to support the model expert in choosing the most appropriate plan depending on the importance of each objective at configuration time.Ministerio de Ciencia e Innovación TIN2009-1371

Generating optimized configurable business process models in scenarios subject to uncertainty

Context: The quality of business process models (i.e., software artifacts that capture the relations between the organizational units of a business) is essential for enhancing the management of business processes. However, such modeling is typically carried out manually. This is already challenging and time consuming when (1) input uncertainty exists, (2) activities are related, and (3) resource allocation has to be considered. When including optimization requirements regarding flexibility and robustness it becomes even more complicated potentially resulting into non-optimized models, errors, and lack of flexibility. Objective: To facilitate the human work and to improve the resulting models in scenarios subject to uncertainty, we propose a software-supported approach for automatically creating configurable business process models from declarative specifications considering all the aforementioned requirements. Method: First, the scenario is modeled through a declarative language which allows the analysts to specify its variability and uncertainty. Thereafter, a set of optimized enactment plans (each one representing a potential execution alternative) are generated from such a model considering the input uncertainty. Finally, to deal with this uncertainty during run-time, a flexible configurable business process model is created from these plans. Results: To validate the proposed approach, we conduct a case study based on a real business which is subject to uncertainty. Results indicate that our approach improves the actual performance of the business and that the generated models support most of the uncertainty inherent to the business. Conclusions: The proposed approach automatically selects the best part of the variability of a declarative specification. Unlike existing approaches, our approach considers input uncertainty, the optimization of multiple objective functions, as well as the resource and the control-flow perspectives. However, our approach also presents a few limitations: (1) it is focused on the control-flow and the data perspective is only partially addressed and (2) model attributes need to be estimated.Ministerio de Ciencia e Innovación TIN2009-1371

Flexible runtime support of business processes under rolling planning horizons

This work has been motivated by the needs we discovered when analyzing real-world processes from the healthcare domain that have revealed high flexibility demands and complex temporal constraints. When trying to model these processes with existing languages, we learned that none of the latter was able to fully address these needs. This motivated us to design TConDec-R, a declarative process modeling language enabling the specification of complex temporal constraints. Enacting business processes based on declarative process models, however, introduces a high complexity due to the required optimization of objective functions, the handling of various temporal constraints, the concurrent execution of multiple process instances, the management of crossinstance constraints, and complex resource allocations. Consequently, advanced user support through optimized schedules is required when executing the instances of such models. In previous work, we suggested a method for generating an optimized enactment plan for a given set of process instances created from a TConDec-R model. However, this approach was not applicable to scenarios with uncertain demands in which the enactment of newly created process instances starts continuously over time, as in the considered healthcare scenarios. Here, the process instances to be planned within a specific timeframe cannot be considered in isolation from the ones planned for future timeframes. To be able to support such scenarios, this article significantly extends our previous work by generating optimized enactment plans under a rolling planning horizon. We evaluate the approach by applying it to a particularly challenging healthcare process scenario, i.e., the diagnostic procedures required for treating patients with ovarian carcinoma in a Woman Hospital. The application of the approach to this sophisticated scenario allows avoiding constraint violations and effectively managing shared resources, which contributes to reduce the length of patient stays in the hospital.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Ciencia e Innovación PID2019-105455 GB-C3

Geochemistry of Platinum-Group Elements (PGE) in Cerro Matoso and Planeta Rica Ni-Laterite deposits, Northern Colombia

Platinum-group elements (PGE) are included among the so-called critical metals, and are essential metals for the technological industry. However, there are very few deposits in the world from which these metals can be extracted. The present work investigates three Ni-laterite profiles (hydrous Mg silicate type) formed over the ultramafic rocks of Cerro Matoso and Planeta Rica in Colombia. The main goal is to determine their PGE concentration and distribution, as well as to identify the carrier phases of these noble metals. The highest PGE contents in Cerro Matoso and Planeta Rica are concentrated in the limonite horizon (141-272 ppb), showing a strong decrease towards the saprolite and the underlying serpentinized peridotite (parent rock; Ru>Pd and the lowest to Rh<Os<Ir. Such distribution indicates that PGE are mobilized in different proportions by the laterization processes. The high affinity between PGE and Fe favors the formation of PGE-Fe mineral alloys such as the Pt-Ir-Fe-Ni minerals hosted by Fe-oxyhydroxide found in the limonite-saprolite transition zone in Planeta Rica. In addition, in the same zone, nanoparticles of Pt (< 1 μm) were found within framboidal pyrite. Both types of platinum group minerals (PGM) are secondary in origin. In the case of Pt-Ir-Fe-Ni alloys, this interpretation is supported by their morphology and chemical composition, which is comparable with PGE-Fe-Ni alloys found in laterites of Dominican Republic. In the case of Pt nanoparticle, textural relations suggest the neoformation of PGM adhered to the porous edges of altered pyrite. Cerro Matoso and Planeta Rica should be considered as unconventional PGE deposits, if adequate recovery processes can be applied for their recovery as by-products during Ni (+Co) production

etrological, geochemical (major, trace, and rare earth elements), and U–Pb zircon data of the Tamatán Group, NE Mexico

From samples of the Paleozoic Tamatán Group (Huizachal–Peregrina Anticlinorium, Tamaulipas, Mexico), petrographic (qualitative and modal) and geochemical analyses (major, trace, and rare earth elements) were conducted. The first U–Pb geochronological data on detrital zircons of the Tamatán Group were generated using four samples. The data presented here contains a broad overview of photomicrography, recalculated modal point-count data, raw geochemical data, and simple statistics of selected geochemical parameters. The data presented in this article are interpreted and discussed in the research article titled “Provenance and tectonic setting of the Tamatán Paleozoic sequence, NE Mexico: Implications for the closure of the Rheic Ocean at the northwestern part of Gondwana”publishedVersio

Time Prediction on Multi-perspective Declarative Business Processes

Process-aware information systems (PAISs) are increasingly used to provide flexible support for business processes. The support given through a PAIS is greatly enhanced when it is able to provide accurate time predictions which is typically a very challenging task. Predictions should be (1) multi-dimensional and (2) not based on a single process instance. Furthermore, the prediction system should be able to (3) adapt to changing circumstances and (4) deal with multi-perspective declarative languages (e.g., models which consider time, resource, data and control flow perspectives). In this work, a novel approach for generating time predictions considering the aforementioned characteristics is proposed. For this, first, a multi-perspective constraint-based language is used to model the scenario. Thereafter, an optimized enactment plan (representing a potential execution alternative) is generated from such a model considering the current execution state of the process instances. Finally, pre-dictions are performed by evaluating a desired function over this enactment plan. To evaluate the applicability of our approach in practical settings we apply it to a real process scenario. Despite the high complexity of the considered problems, results indicate that our approach produces a satisfactory number of good predictions in a reasonable time.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71618-