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Chance-Constrained Efficiency Analysis
Data envelopment analysis (DEA) is extended to the case of stochastic inputs and outputs through the use of chance-constrained programming. The chance-constrained envelope envelops a given set of observations "most of the time." We show that the chance-constrained enveloping process leads to the definition of a conventional (certainty-equivalent) efficiency ratio (a ratio between weighted outputs and weighted inputs). Furthermore, extending the concept of Pareto and Koopmans efficiency to the case of chance-constrained dominance (to be defined), we establish the identity of the following two chance-constrained efficiency concepts: (i) the chance constrained DEA efficiency measure of a particular output-input point is unity, and all chance-constraints are binding; (ii) the point is efficient in the sense Pareto and Koopmans. Finally we discuss the implications of our approach for econometric frontier analysis.IC2 Institut
Composition and Self-Adaptation of Service-Based Systems with Feature Models
The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932,
TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by
Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and
P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tec
A Product Line Systems Engineering Process for Variability Identification and Reduction
Software Product Line Engineering has attracted attention in the last two
decades due to its promising capabilities to reduce costs and time to market
through reuse of requirements and components. In practice, developing system
level product lines in a large-scale company is not an easy task as there may
be thousands of variants and multiple disciplines involved. The manual reuse of
legacy system models at domain engineering to build reusable system libraries
and configurations of variants to derive target products can be infeasible. To
tackle this challenge, a Product Line Systems Engineering process is proposed.
Specifically, the process extends research in the System Orthogonal Variability
Model to support hierarchical variability modeling with formal definitions;
utilizes Systems Engineering concepts and legacy system models to build the
hierarchy for the variability model and to identify essential relations between
variants; and finally, analyzes the identified relations to reduce the number
of variation points. The process, which is automated by computational
algorithms, is demonstrated through an illustrative example on generalized
Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of
the process in the reduction of variation points, it is further applied to case
studies in different engineering domains at different levels of complexity.
Subject to system model availability, reduction of 14% to 40% in the number of
variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal
on 3rd June 201
Extending the production dice game.
The production dice game is a powerful learning exercise focusing on the impact of variability and dependency on throughput and work-in-process inventory of flow lines. In this paper we will extend the basic dice game along the following lines. First, we allow that the operations take place concurrently as opposed to the more traditional way of playing the game sequentially. Second, we allow both starvation and blocking of the line. Third, we consider balanced lines with work stations characterized by different degrees of variability. Fourth, we use different sets of dice in order to represent a wide range of coefficients of variation of the production line. The game can be played manually in a classroom setting, but it is also modelled as an easy-to-use simulation tool.
PICES Press, Vol. 12, No. 1, January 2004
The state of PICES science - 2003 (pdf 281 KB)
2003 Wooster Award (pdf 764 KB)
The state of the eastern North Pacific through summer 2003 (pdf 448 KB)
The Bering Sea: Current status and recent events (pdf 951 KB)
The state of the western North Pacific in the first half of 2003 (pdf 684 KB)
The status of oceanic zooplankton in the eastern North Pacific (pdf 390 KB)
The precautionary approach to the PDO (pdf 976 KB)
Photo highlights of PICES XII (pdf 2.79 MB)
William G. Pearcy: Renaissance oceanographer (pdf 2.86 MB)
KORDI/PICES/CoML Workshop on "Variability and status of the Yellow Sea and East China Sea ecosystems (pdf 785 KB)
PICES/IOC Workshop on "Harmful algal blooms - Harmonization of data" (pdf 330 KB)
From physics to predators: Monitoring North Pacific ecosystem dynamics (pdf 270 KB)
Toward a coast-wide network of Northeast Pacific coastal-ocean monitoring programs - a brief workshop report (pdf 640)
PICES publications (pdf 103 KB)
PICES calendar (pdf 45 KB
Last planner and critical chain in construction management: comparative analysis
This paper endeavours to compare the Last Planner System of production control and the Critical Chain production management method. This comparison is carried out in the context of construction management. The original prescription and the evolution of the practice are examined regarding both approaches, and the similarities and differences are noted. Based on these considerations, gaps in the two approaches are identified and the potential of a synthesis of them is explored
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