21,731 research outputs found
A Component Based Heuristic Search Method with Evolutionary Eliminations
Nurse rostering is a complex scheduling problem that affects hospital
personnel on a daily basis all over the world. This paper presents a new
component-based approach with evolutionary eliminations, for a nurse scheduling
problem arising at a major UK hospital. The main idea behind this technique is
to decompose a schedule into its components (i.e. the allocated shift pattern
of each nurse), and then to implement two evolutionary elimination strategies
mimicking natural selection and natural mutation process on these components
respectively to iteratively deliver better schedules. The worthiness of all
components in the schedule has to be continuously demonstrated in order for
them to remain there. This demonstration employs an evaluation function which
evaluates how well each component contributes towards the final objective. Two
elimination steps are then applied: the first elimination eliminates a number
of components that are deemed not worthy to stay in the current schedule; the
second elimination may also throw out, with a low level of probability, some
worthy components. The eliminated components are replenished with new ones
using a set of constructive heuristics using local optimality criteria.
Computational results using 52 data instances demonstrate the applicability of
the proposed approach in solving real-world problems.Comment: 27 pages, 4 figure
Metamodel Instance Generation: A systematic literature review
Modelling and thus metamodelling have become increasingly important in
Software Engineering through the use of Model Driven Engineering. In this paper
we present a systematic literature review of instance generation techniques for
metamodels, i.e. the process of automatically generating models from a given
metamodel. We start by presenting a set of research questions that our review
is intended to answer. We then identify the main topics that are related to
metamodel instance generation techniques, and use these to initiate our
literature search. This search resulted in the identification of 34 key papers
in the area, and each of these is reviewed here and discussed in detail. The
outcome is that we are able to identify a knowledge gap in this field, and we
offer suggestions as to some potential directions for future research.Comment: 25 page
Predictive Control of Autonomous Kites in Tow Test Experiments
In this paper we present a model-based control approach for autonomous flight
of kites for wind power generation. Predictive models are considered to
compensate for delay in the kite dynamics. We apply Model Predictive Control
(MPC), with the objective of guiding the kite to follow a figure-of-eight
trajectory, in the outer loop of a two level control cascade. The tracking
capabilities of the inner-loop controller depend on the operating conditions
and are assessed via a frequency domain robustness analysis. We take the
limitations of the inner tracking controller into account by encoding them as
optimisation constraints in the outer MPC. The method is validated on a kite
system in tow test experiments.Comment: The paper has been accepted for publication in the IEEE Control
Systems Letters and is subject to IEEE Control Systems Society copyright.
Upon publication, the copy of record will be available at
http://ieeexplore.ieee.or
AUTOMATIC TEST GENERATION BASED ON CONSTRAINTS
It seems to be a very hard task to enhance the properties of widespreadly used automatic test pattern generation algorithms. Experiences show that achievements are sometimes not worth the effort. In the authors' opinion this fact stems from the basically 'algorithm oriented' nature of research made in the past. A new experimental framework is presented for the problem, considering network representation and search control algorithms
as equally important parts. The network is represented by object- oriented data-flow networks, the search control algorithm is based on constraint satisfaction, and a special kind of dependency directed backtracking which we call constraint slackening. Similar methods were proved to be very useful in automatic system diagnosis by DAVIS (1985) and others, although have not been introduced to testing yet. This paper summarises the basic notions of constraint satisfaction, the potential advantages of using it for building test generation systems, and shows implementational details of a test generation system, based on constraints. Experiences of the run-time tests show that constraint-based test generation can be highly efficient
- …