132 research outputs found
A Compact Linear Programming Relaxation for Binary Sub-modular MRF
We propose a novel compact linear programming (LP) relaxation for binary
sub-modular MRF in the context of object segmentation. Our model is obtained by
linearizing an -norm derived from the quadratic programming (QP) form of
the MRF energy. The resultant LP model contains significantly fewer variables
and constraints compared to the conventional LP relaxation of the MRF energy.
In addition, unlike QP which can produce ambiguous labels, our model can be
viewed as a quasi-total-variation minimization problem, and it can therefore
preserve the discontinuities in the labels. We further establish a relaxation
bound between our LP model and the conventional LP model. In the experiments,
we demonstrate our method for the task of interactive object segmentation. Our
LP model outperforms QP when converting the continuous labels to binary labels
using different threshold values on the entire Oxford interactive segmentation
dataset. The computational complexity of our LP is of the same order as that of
the QP, and it is significantly lower than the conventional LP relaxation
Lower Critical Dimension of Ising Spin Glasses
Exact ground states of two-dimensional Ising spin glasses with Gaussian and
bimodal (+- J) distributions of the disorder are calculated using a
``matching'' algorithm, which allows large system sizes of up to N=480^2 spins
to be investigated. We study domain walls induced by two rather different types
of boundary-condition changes, and, in each case, analyze the system-size
dependence of an appropriately defined ``defect energy'', which we denote by
DE. For Gaussian disorder, we find a power-law behavior DE ~ L^\theta, with
\theta=-0.266(2) and \theta=-0.282(2) for the two types of boundary condition
changes. These results are in reasonable agreement with each other, allowing
for small systematic effects. They also agree well with earlier work on smaller
sizes. The negative value indicates that two dimensions is below the lower
critical dimension d_c. For the +-J model, we obtain a different result, namely
the domain-wall energy saturates at a nonzero value for L\to \infty, so \theta
= 0, indicating that the lower critical dimension for the +-J model exactly
d_c=2.Comment: 4 pages, 4 figures, 1 table, revte
Ground-State Roughness of the Disordered Substrate and Flux Line in d=2
We apply optimization algorithms to the problem of finding ground states for
crystalline surfaces and flux lines arrays in presence of disorder. The
algorithms provide ground states in polynomial time, which provides for a more
precise study of the interface widths than from Monte Carlo simulations at
finite temperature. Using systems up to size , with a minimum of
realizations at each size, we find very strong evidence for a
super-rough state at low temperatures.Comment: 10 pages, 3 PS figures, to appear in PR
Statistical Topography of Glassy Interfaces
Statistical topography of two-dimensional interfaces in the presence of
quenched disorder is studied utilizing combinatorial optimization algorithms.
Finite-size scaling is used to measure geometrical exponents associated with
contour loops and fully packed loops. We find that contour-loop exponents
depend on the type of disorder (periodic ``vs'' non-periodic) and they satisfy
scaling relations characteristic of self-affine rough surfaces. Fully packed
loops on the other hand are unaffected by disorder with geometrical exponents
that take on their pure values.Comment: 4 pages, REVTEX, 4 figures included. Further information can be
obtained from [email protected]
No spin-glass transition in the "mobile-bond" model
The recently introduced ``mobile-bond'' model for two-dimensional spin
glasses is studied. The model is characterized by an annealing temperature T_q.
On the basis of Monte Carlo simulations of small systems it has been claimed
that this model exhibits a non-trivial spin-glass transition at finite
temperature for small values of T_q.
Here the model is studied by means of exact ground-state calculations of
large systems up to N=256^2. The scaling of domain-wall energies is
investigated as a function of the system size. For small values T_q<0.95 the
system behaves like a (gauge-transformed) ferromagnet having a small fraction
of frustrated plaquettes. For T_q>=0.95 the system behaves like the standard
two-dimensional +-J spin-glass, i.e. it does NOT exhibit a phase transition at
T>0.Comment: 4 pages, 5 figures, RevTe
Simulation of the Zero Temperature Behavior of a 3-Dimensional Elastic Medium
We have performed numerical simulation of a 3-dimensional elastic medium,
with scalar displacements, subject to quenched disorder. We applied an
efficient combinatorial optimization algorithm to generate exact ground states
for an interface representation. Our results indicate that this Bragg glass is
characterized by power law divergences in the structure factor . We have found numerically consistent values of the coefficient for
two lattice discretizations of the medium, supporting universality for in
the isotropic systems considered here. We also examine the response of the
ground state to the change in boundary conditions that corresponds to
introducing a single dislocation loop encircling the system. Our results
indicate that the domain walls formed by this change are highly convoluted,
with a fractal dimension . We also discuss the implications of the
domain wall energetics for the stability of the Bragg glass phase. As in other
disordered systems, perturbations of relative strength introduce a new
length scale beyond which the perturbed ground
state becomes uncorrelated with the reference (unperturbed) ground state. We
have performed scaling analysis of the response of the ground state to the
perturbations and obtain . This value is consistent with the
scaling relation , where characterizes the
scaling of the energy fluctuations of low energy excitations.Comment: 20 pages, 13 figure
Generating droplets in two-dimensional Ising spin glasses by using matching algorithms
We study the behavior of droplets for two dimensional Ising spin glasses with
Gaussian interactions. We use an exact matching algorithm which enables study
of systems with linear dimension L up to 240, which is larger than is possible
with other approaches. But the method only allows certain classes of droplets
to be generated. We study single-bond, cross and a category of fixed volume
droplets as well as first excitations. By comparison with similar or equivalent
droplets generated in previous works, the advantages but also the limitations
of this approach are revealed. In particular we have studied the scaling
behavior of the droplet energies and droplet sizes. In most cases, a crossover
of the data can be observed such that for large sizes the behavior is
compatible with the one-exponent scenario of the droplet theory. Only for the
case of first excitations, no clear conclusion can be reached, probably because
even with the matching approach the accessible system sizes are still too
small.Comment: 11 pages, 16 figures, revte
Rail-freight crew scheduling with a genetic algorithm
peer reviewedThis article presents a novel genetic algorithm designed for the solution
of the Crew Scheduling Problem (CSP) in the rail-freight industry. CSP is the task
of assigning drivers to a sequence of train trips while ensuring that no driver’s
schedule exceeds the permitted working hours, that each driver starts and finishes
their day’s work at the same location, and that no train routes are left without a
driver. Real-life CSPs are extremely complex due to the large number of trips,
opportunities to use other means of transportation, and numerous government
regulations and trade union agreements. CSP is usually modelled as a set-covering
problem and solved with linear programming methods. However, the sheer
volume of data makes the application of conventional techniques computationally
expensive, while existing genetic algorithms often struggle to handle the large
number of constraints. A genetic algorithm is presented that overcomes these
challenges by using an indirect chromosome representation and decoding
procedure. Experiments using real schedules on the UK national rail network
show that the algorithm provides an effective solution within a faster timeframe
than alternative approaches
Fuzzy-logic controlled genetic algorithm for the rail-freight crew-scheduling problem
AbstractThis article presents a fuzzy-logic controlled genetic algorithm designed for the solution of the crew-scheduling problem in the rail-freight industry. This problem refers to the assignment of train drivers to a number of train trips in accordance with complex industrial and governmental regulations. In practice, it is a challenging task due to the massive quantity of train trips, large geographical span and significant number of restrictions. While genetic algorithms are capable of handling large data sets, they are prone to stalled evolution and premature convergence on a local optimum, thereby obstructing further search. In order to tackle these problems, the proposed genetic algorithm contains an embedded fuzzy-logic controller that adjusts the mutation and crossover probabilities in accordance with the genetic algorithm’s performance. The computational results demonstrate a 10% reduction in the cost of the schedule generated by this hybrid technique when compared with a genetic algorithm with fixed crossover and mutation rates
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