Extensible Automated Constraint Modelling

In constraint solving, a critical bottleneck is the formulationof an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE. A set of rules is used to refine an abstract specification into a concrete constraint model. We demonstrate that this set of rules is readily extensible to increase the space of possible constraint models CONJURE can produce. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 32 benchmark problems found in the literature

CONJURE: automatic generation of constraint models from problem specifications

Funding: Engineering and Physical Sciences Research Council (EP/V027182/1, EP/P015638/1), Royal Society (URF/R/180015).When solving a combinatorial problem, the formulation or model of the problem is critical tothe efficiency of the solver. Automating the modelling process has long been of interest because of the expertise and time required to produce an effective model of a given problem. We describe a method to automatically produce constraint models from a problem specification written in the abstract constraint specification language Essence. Our approach is to incrementally refine the specification into a concrete model by applying a chosen refinement rule at each step. Any nontrivial specification may be refined in multiple ways, creating a space of models to choose from. The handling of symmetries is a particularly important aspect of automated modelling. Many combinatorial optimisation problems contain symmetry, which can lead to redundant search. If a partial assignment is shown to be invalid, we are wasting time if we ever consider a symmetric equivalent of it. A particularly important class of symmetries are those introduced by the constraint modelling process: modelling symmetries. We show how modelling symmetries may be broken automatically as they enter a model during refinement, obviating the need for an expensive symmetry detection step following model formulation. Our approach is implemented in a system called Conjure. We compare the models producedby Conjure to constraint models from the literature that are known to be effective. Our empirical results confirm that Conjure can reproduce successfully the kernels of the constraint models of 42 benchmark problems found in the literature.Publisher PDFPeer reviewe

Filtering Algorithms for the Multiset Ordering Constraint

Constraint programming (CP) has been used with great success to tackle a wide variety of constraint satisfaction problems which are computationally intractable in general. Global constraints are one of the important factors behind the success of CP. In this paper, we study a new global constraint, the multiset ordering constraint, which is shown to be useful in symmetry breaking and searching for leximin optimal solutions in CP. We propose efficient and effective filtering algorithms for propagating this global constraint. We show that the algorithms are sound and complete and we discuss possible extensions. We also consider alternative propagation methods based on existing constraints in CP toolkits. Our experimental results on a number of benchmark problems demonstrate that propagating the multiset ordering constraint via a dedicated algorithm can be very beneficial

CMBPol Mission Concept Study: Foreground Science Knowledge and Prospects

We report on our knowledge of Galactic foregrounds, as well as on how a CMB satellite mission aiming at detecting a primordial B-mode signal (CMBPol) will contribute to improving it. We review the observational and analysis techniques used to constrain the structure of the Galactic magnetic field, whose presence is responsible for the polarization of Galactic emissions. Although our current understanding of the magnetized interstellar medium is somewhat limited, dramatic improvements in our knowledge of its properties are expected by the time CMBPol flies. Thanks to high resolution and high sensitivity instruments observing the whole sky at frequencies between 30 GHz and 850 GHz, CMBPol will not only improve this picture by observing the synchrotron emission from our galaxy, but also help constrain dust models. Polarized emission from interstellar dust indeed dominates over any other signal in CMBPol's highest frequency channels. Observations at these wavelengths, combined with ground-based studies of starlight polarization, will therefore enable us to improve our understanding of dust properties and of the mechanism(s) responsible for the alignment of dust grains with the Galactic magnetic field. CMBPol will also shed new light on observations that are presently not well understood. Morphological studies of anomalous dust and synchrotron emissions will indeed constrain their natures and properties, while searching for fluctuations in the emission from heliospheric dust will test our understanding of the circumheliospheric interstellar medium. Finally, acquiring more information on the properties of extra-Galactic sources will be necessary in order to maximize the cosmological constraints extracted from CMBPol's observations of CMB lensing. (abridged)Comment: 43 pages, 7 figures, 2 table

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed