2,367 research outputs found
Efficiency Analysis of Swarm Intelligence and Randomization Techniques
Swarm intelligence has becoming a powerful technique in solving design and
scheduling tasks. Metaheuristic algorithms are an integrated part of this
paradigm, and particle swarm optimization is often viewed as an important
landmark. The outstanding performance and efficiency of swarm-based algorithms
inspired many new developments, though mathematical understanding of
metaheuristics remains partly a mystery. In contrast to the classic
deterministic algorithms, metaheuristics such as PSO always use some form of
randomness, and such randomization now employs various techniques. This paper
intends to review and analyze some of the convergence and efficiency associated
with metaheuristics such as firefly algorithm, random walks, and L\'evy
flights. We will discuss how these techniques are used and their implications
for further research.Comment: 10 pages. arXiv admin note: substantial text overlap with
arXiv:1212.0220, arXiv:1208.0527, arXiv:1003.146
Computational models for inferring biochemical networks
Biochemical networks are of great practical importance. The interaction of biological compounds in cells has been enforced to a proper understanding by the numerous bioinformatics projects, which contributed to a vast amount of biological information. The construction of biochemical systems (systems of chemical reactions), which include both topology and kinetic constants of the chemical reactions, is NP-hard and is a well-studied system biology problem. In this paper, we propose a hybrid architecture, which combines genetic programming and simulated annealing in order to generate and optimize both the topology (the network) and the reaction rates of a biochemical system. Simulations and analysis of an artificial model and three real models (two models and the noisy version of one of them) show promising results for the proposed method.The Romanian National Authority for Scientific Research, CNDI–UEFISCDI,
Project No. PN-II-PT-PCCA-2011-3.2-0917
On the generalised Langevin equation for simulated annealing
In this paper, we consider the generalised (higher order) Langevin equation for the purpose of simulated annealing and optimisation of nonconvex functions. Our approach modifies the underdamped Langevin equation by replacing the Brownian noise with an appropriate Ornstein-Uhlenbeck process to account for memory in the system. Under reasonable conditions on the loss function and the annealing schedule, we establish convergence of the continuous time dynamics to a global minimum. In addition, we investigate the performance numerically and show better performance and higher exploration of the state space compared to the underdamped and overdamped Langevin dynamics with the same annealing schedule
The approximate coordinate exchange algorithm for Bayesian optimal design of experiments
Optimal Bayesian experimental design typically involves maximising the expectation, with respect to the joint distribution of parameters and responses, of some appropriately chosen utility function. This objective function is usually not available in closed form and the design space can be of high dimensionality. The approximate coordinate exchange algorithm is proposed for this maximisation problem where a Gaussian process emulator is used to approximate the objective function. The algorithm can be used for arbitrary utility functions meaning we can consider fully Bayesian optimal design. It can also be used for those utility functions that result in pseudo-Bayesian designs such as the popular Bayesian D-optimality. The algorithm is demonstrated on a range of examples
Out of equilibrium dynamics of classical and quantum complex systems
Equilibrium is a rather ideal situation, the exception rather than the rule
in Nature. Whenever the external or internal parameters of a physical system
are varied its subsequent relaxation to equilibrium may be either impossible or
take very long times. From the point of view of fundamental physics no generic
principle such as the ones of thermodynamics allows us to fully understand
their behaviour. The alternative is to treat each case separately. It is
illusionary to attempt to give, at least at this stage, a complete description
of all non-equilibrium situations. Still, one can try to identify and
characterise some concrete but still general features of a class of out of
equilibrium problems - yet to be identified - and search for a unified
description of these. In this report I briefly describe the behaviour and
theory of a set of non-equilibrium systems and I try to highlight common
features and some general laws that have emerged in recent years.Comment: 36 pages, to be published in Compte Rendus de l'Academie de Sciences,
T. Giamarchi e
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