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Handling boundary constraints for particle swarm optimization in high-dimensional search space
Despite the fact that the popular particle swarm optimizer (PSO) is currently being extensively applied to many real-world problems that often have high-dimensional and complex fitness landscapes, the effects of boundary constraints on PSO have not attracted adequate attention in the literature. However, in accordance with the theoretical analysis in [11], our numerical experiments show that particles tend to fly outside of the boundary in the first few iterations at a very high probability in high-dimensional search spaces. Consequently, the method used to handle boundary violations is critical to the performance of PSO. In this study, we reveal that the widely used random and absorbing bound-handling schemes may paralyze PSO for high-dimensional and complex problems. We also explore in detail the distinct mechanisms responsible for the failures of these two bound-handling schemes. Finally, we suggest that using high-dimensional and complex benchmark functions, such as the composition functions in [19], is a prerequisite to identifying the potential problems in applying PSO to many real-world applications because certain properties of standard benchmark functions make problems inexplicit. © 2011 Elsevier Inc. All rights reserved
Parameter estimation in spatially extended systems: The Karhunen-Loeve and Galerkin multiple shooting approach
Parameter estimation for spatiotemporal dynamics for coupled map lattices and
continuous time domain systems is shown using a combination of multiple
shooting, Karhunen-Loeve decomposition and Galerkin's projection methodologies.
The resulting advantages in estimating parameters have been studied and
discussed for chaotic and turbulent dynamics using small amounts of data from
subsystems, availability of only scalar and noisy time series data, effects of
space-time parameter variations, and in the presence of multiple time-scales.Comment: 11 pages, 5 figures, 4 Tables Corresponding Author - V. Ravi Kumar,
e-mail address: [email protected]
Shaping Current Waveforms for direct Modulation of Semiconductor Lasers
We demonstrate a technique for shaping current inputs for the direct
modulation of a semiconductor laser for digital communication. The introduction
of shaped current inputs allows for the suppression of relaxation oscillations
and the avoidance of dynamical memory in the physical laser device, i.e., the
output will not be influenced by previously communicated information. On the
example of time-optimized bits, the possible performance enhancement for high
data rate communications is shown numerically.Comment: 8 pages, 6 figures, to be published in IEEE Journal of Quantum
Electronic
Optimization in Networks
The recent surge in the network modeling of complex systems has set the stage
for a new era in the study of fundamental and applied aspects of optimization
in collective behavior. This Focus Issue presents an extended view of the state
of the art in this field and includes articles from a large variety of domains
where optimization manifests itself, including physical, biological, social,
and technological networked systems.Comment: Opening article of the CHAOS Focus Issue "Optimization in Networks",
available at http://link.aip.org/link/?CHA/17/2/htmlto
Seeking Quantum Speedup Through Spin Glasses: The Good, the Bad, and the Ugly
There has been considerable progress in the design and construction of
quantum annealing devices. However, a conclusive detection of quantum speedup
over traditional silicon-based machines remains elusive, despite multiple
careful studies. In this work we outline strategies to design hard tunable
benchmark instances based on insights from the study of spin glasses - the
archetypal random benchmark problem for novel algorithms and optimization
devices. We propose to complement head-to-head scaling studies that compare
quantum annealing machines to state-of-the-art classical codes with an approach
that compares the performance of different algorithms and/or computing
architectures on different classes of computationally hard tunable spin-glass
instances. The advantage of such an approach lies in having to only compare the
performance hit felt by a given algorithm and/or architecture when the instance
complexity is increased. Furthermore, we propose a methodology that might not
directly translate into the detection of quantum speedup, but might elucidate
whether quantum annealing has a "`quantum advantage" over corresponding
classical algorithms like simulated annealing. Our results on a 496 qubit
D-Wave Two quantum annealing device are compared to recently-used
state-of-the-art thermal simulated annealing codes.Comment: 14 pages, 8 figures, 3 tables, way too many reference
Frameworks for Strategic Leadership
I suggest two frameworks that may improve understanding of strategic thinking, strategic decision making, and strategic leadership. The first I call the Epistemology Framework. The second which was described and continues to be promoted by David Snowdon and colleagues is the Cynefin Framework
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