17,811 research outputs found
On the Effectiveness of Genetic Search in Combinatorial Optimization
In this paper, we study the efficacy of genetic algorithms in the context of combinatorial optimization. In particular, we isolate the effects of cross-over, treated as the central component of genetic search. We show that for problems of nontrivial size and difficulty, the contribution of cross-over search is marginal, both synergistically when run in conjunction with mutation and selection, or when run with selection alone, the reference point being the search procedure consisting of just mutation and selection. The latter can be viewed as another manifestation of the Metropolis process. Considering the high computational cost of maintaining a population to facilitate cross-over search, its marginal benefit renders genetic search inferior to its singleton-population counterpart, the Metropolis process, and by extension, simulated annealing. This is further compounded by the fact that many problems arising in practice may inherently require a large number of state transitions for a near-optimal solution to be found, making genetic search infeasible given the high cost of computing a single iteration in the enlarged state-space.NSF (CCR-9204284
Minimum entropy restoration using FPGAs and high-level techniques
One of the greatest perceived barriers to the widespread use of FPGAs in image processing is the difficulty for application specialists of developing algorithms on reconfigurable hardware. Minimum entropy deconvolution (MED) techniques have been shown to be effective in the restoration of star-field images. This paper reports on an attempt to implement a MED algorithm using simulated annealing, first on a microprocessor, then on an FPGA. The FPGA implementation uses DIME-C, a C-to-gates compiler, coupled with a low-level core library to simplify the design task. Analysis of the C code and output from the DIME-C compiler guided the code optimisation. The paper reports on the design effort that this entailed and the resultant performance improvements
Simulated Annealing for JPEG Quantization
JPEG is one of the most widely used image formats, but in some ways remains
surprisingly unoptimized, perhaps because some natural optimizations would go
outside the standard that defines JPEG. We show how to improve JPEG compression
in a standard-compliant, backward-compatible manner, by finding improved
default quantization tables. We describe a simulated annealing technique that
has allowed us to find several quantization tables that perform better than the
industry standard, in terms of both compressed size and image fidelity.
Specifically, we derive tables that reduce the FSIM error by over 10% while
improving compression by over 20% at quality level 95 in our tests; we also
provide similar results for other quality levels. While we acknowledge our
approach can in some images lead to visible artifacts under large
magnification, we believe use of these quantization tables, or additional
tables that could be found using our methodology, would significantly reduce
JPEG file sizes with improved overall image quality.Comment: Appendix not included in arXiv version due to size restrictions. For
full paper go to:
http://www.eecs.harvard.edu/~michaelm/SimAnneal/PAPER/simulated-annealing-jpeg.pd
Multicanonical Methods vs. Molecular Dynamics vs. Monte Carlo: Comparison for Lennard-Jones Glasses
We applied a multicanonical algorithm (entropic sampling) to a
two-dimensional and a three-dimensional Lennard-Jones system with
quasicrystalline and glassy ground states. Focusing on the ability of the
algorithm to locate low lying energy states, we compared the results of the
multicanonical simulations with standard Monte Carlo simulated annealing and
molecular dynamics methods. We find slight benefits to using entropic sampling
in small systems (less than 80 particles), which disappear with larger systems.
This is disappointing as the multicanonical methods are designed to surmount
energy barriers to relaxation. We analyze this failure theoretically, and show
(1) the multicanonical method is reduced in the thermodynamic limit (large
systems) to an effective Monte Carlo simulated annealing with a random
temperature vs. time, and (2) the multicanonical method gets trapped by
unphysical entropy barriers in the same metastable states whose energy barriers
trap the traditional quenches. The performance of Monte Carlo and molecular
dynamics quenches were remarkably similar.Comment: 12 pages, 6 figures, REVTEX, epsf.st
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