Robust Multi-criteria Service Composition in Information Systems

Service compositions are used to implement business processes in a variety of application domains. A quality of service (QoS)-aware selection of the service to be composed involves multiple, usually conflicting and possibly uncertain QoS attributes. A multi-criteria solution approach is desired to generate a set of alternative service selections. In addition, the uncertainty of QoSattributes is neglected in existing solution approaches. Hence, the need for service reconfigurations is imposed to avoid the violation of QoS restrictions. The researched problem is NP-hard. This article presents a heuristic multicriteria service selection approach that is designed to determine a Pareto frontier of alternative service selections in a reasonable amount of time. Taking into account the uncertainty of response times, the obtained service selections are robust with respect to the constrained execution time. The proposed solution approach is based on the Nondominated Sorting Genetic Algorithm (NSGA)-II extended by heuristics that exploit problem specific characteristics of the QoS-aware service selection. The applicability of the solution approach is demonstrated by a simulation study

Heuristiken zur multikriteriellen Komposition von Diensten in dienstbasierten Informationssystemen

Service-orientierte Architekturen unterstützen die Bereitstellung von Anwendungsfunktionalität durch Dienstkomposition. Dabei werden nicht-funktionale Attribute betrachtet, um zwischen funk-tional gleichwertigen Diensten zu unterscheiden. Wir untersuchen die Auswahl von Diensten aus einer Menge von Dienstkandidaten für den Fall einer sequentiellen Komposition, so dass die Kosten des komponierten Dienstes eine vorgegebene Schranke nicht überschreiten und gleichzeitig die Ausführungszeit minimiert und die Verfügbarkeit des komponierten Dienstes maximiert wird. Da dieses Problem NP-schwer ist, wird ein genetischer Algorithmus zur Ermittlung der Menge von Pareto-optimalen Lösungen vorgeschlagen, der mit problemspezifischen Heuristiken kombiniert wird. Die Ergebnisse numerischer Experimente mit zufällig erzeugten Probleminstanzen zeigen die Leistungsfähigkeit des Ansatzes

A simulation framework for the performance assessment of shop-floor control systems

The authors discuss the concept and design criteria for a framework that facilitates the performance assessment of shop-floo control systems. Their basic concept includes a simulation model that emulates the shop floo of a wafer fab, sends information to the control system, and eceives information back from the control system. The shop-floo control system is realized as a separate module that interfaces to the simulator via a data layer that contains the current shop-floo status and the control information generated by the controller. The authors provide detailed information on how the simulation model and shop-floo control system communicate and how each system triggers events in the other system. They show how this framework supports the performance assessment of the shop-floo control system under consideration. They also present a prototype of the framework currently implemented in the course of the SRC/International Sematech FORCe project "Scheduling of Semiconductor Wafer Fabrication Facilities.

Mutant CEBPA directly drives the expression of the targetable tumor-promoting factor CD73 in AML

The key myeloid transcription factor (TF), CEBPA, is frequently mutated in acute myeloid leukemia (AML), but the direct molecular effects of this leukemic driver mutation remain elusive. To investigate mutant AML, we performed microscale, in vivo chromatin immunoprecipitation sequencing and identified a set of aberrantly activated enhancers, exclusively occupied by the leukemia-associated CEBPA-p30 isoform. Comparing gene expression changes in human mutant AML and the corresponding mouse model, we identified , encoding CD73, as a cross-species AML gene with an upstream leukemic enhancer physically and functionally linked to the gene. Increased expression of CD73, mediated by the CEBPA-p30 isoform, sustained leukemic growth via the CD73/A2AR axis. Notably, targeting of this pathway enhanced survival of AML-transplanted mice. Our data thus indicate a first-in-class link between a cancer driver mutation in a TF and a druggable, direct transcriptional target

Hybrid algorithms for the earliness–tardiness single-machine multiple orders per job scheduling problem with a common due date

In this paper, we study an earliness–tardiness scheduling problem for a single machine that is motivated by process conditions found in semiconductor wafer fabrication facilities (wafer fabs). In modern 300-mm wafer fabs, front opening unified pods (FOUPs) transfer wafers. The number of FOUPs is limited to avoid a congestion of the Automated Material Handling System. Several orders can be grouped in one FOUP. A nonrestrictive common due date for all the orders is assumed. Only orders that belong to the same family can be processed together in a single FOUP at the same time. We present a Mixed Integer Linear Programming (MILP) formulation for this problem. Moreover, we show that this scheduling problem is NP-hard. We propose several simple heuristics based on dispatching rules and assignment strategies from bin packing. Moreover, genetic algorithms are designed that assign the orders to the set of early and tardy orders, respectively. In addition, a random key genetic algorithm (RKGA) is described that proposes order sequences. The different algorithms are hybridized with job formation and sequencing heuristics. A more specialized algorithm that is based on the generalized assignment problem is presented for the special case of a single order family. Results of computational experiments based on randomly generated problem instances are presented. They demonstrate that the genetic algorithms perform well with respect to solution quality and computing time under a broad range of experimental conditions