A comprehensive literature classification of simulation optimisation methods

Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measureSimulation Optimization, classification methods, literature survey

Simulation optimization: A comprehensive review on theory and applications

For several decades, simulation has been used as a descriptive tool by the operations research community in the modeling and analysis of a wide variety of complex real systems. With recent developments in simulation optimization and advances in computing technology, it now becomes feasible to use simulation as a prescriptive tool in decision support systems. In this paper, we present a comprehensive survey on techniques for simulation optimization with emphasis given on recent developments. We classify the existing techniques according to problem characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). We discuss the major advantages and possible drawbacks of the different techniques. A comprehensive bibliography and future research directions are also provided in the paper. © "IIE"

Stochastic Approximation Methods for Systems Over an Infinite Horizon

The paper develops efficient and general stochastic approximation (SA) methods for improving the operation of parametrized systems of either the continuous- or discrete-event dynamical systems types and which are of interest over a long time period. For example, one might wish to optimize or improve the stationary (or average cost per unit time) performance by adjusting the systems parameters. The number of applications and the associated literature are increasing at a rapid rate. This is partly due to the increasing activity in computing pathwise derivatives and adapting them to the average-cost problem. Although the original motivation and the examples come from an interest in the infinite-horizon problem, the techniques and results are of general applicability in SA. We present an updating and review of powerful ordinary differential equation-type methods, in a fairly general context, and based on weak convergence ideas. The results and proof techniques are applicable to a wide variety of applications. Exploiting the full potential of these ideas can greatly simplify and extend much current work. Their breadth as well as the relative ease of using the basic ideas are illustrated in detail via typical examples drawn from discrete-event dynamical systems, piecewise deterministic dynamical systems, and a stochastic differential equations model. In these particular illustrations, we use either infinitesimal perturbation analysis-type estimators, mean square derivative-type estimators, or finite-difference type estimators. Markov and non-Markov models are discussed. The algorithms for distributed/asynchronous updating as well as the fully synchronous schemes are developed

The problem of aftereffects in perturbed angular correlation studies of ceria

Perturbed Angular Correlations (PAC) spectroscopy is an effective local probe technique often employed in the characterization of defects or phase transitions in any of a variety of materials. This technique relies upon the ability of probe nuclei to function as gauges of the magnetic fields and electric field gradients local to the probes once they have been introduced (doped) into the lattice in question. It has been seen that disturbances in the electronic environment of the probe nucleus due to, for instance, the presence and movement of electron holes can impair the ability of the probe to function, thereby undermining the efficacy of the approach. This impairment and subsequent distortion of lattice information provided are known as the problem of "aftereffects." In PAC studies of ceria, a poor conductor, disturbances in the electronic environment of the ¹¹¹Cd probe subsequent to electron capture result in bothersome aftereffects in the PAC data spectrum. These aftereffects are believed to be characterizable in terms of two rates: electronic hole hopping and escape. A model that treats the aftereffect in terms of the hopping and escape rates associated with one electronic hole (and which assumes the system is otherwise unperturbed) was tested for · low temperatures (10 K). The data indicate that this aftereffect model as it stands does not describe the behaviour of the system at low temperatures. However, it is clear that the aftereffect problem is exacerbated by low temperatures, though the increase of the fraction of aftereffected sites is not smooth over the temperature range 10-293 K. The problem of aftereffects is pronounced in 0.1% Nb-doped ceria. Typically, room temperature measurements of this system show greater than 70% aftereffected sites. No aftereffect whatsoever was found in 1% In-doped ceria at room temperature

"Rotterdam econometrics": publications of the econometric institute 1956-2005

This paper contains a list of all publications over the period 1956-2005, as reported in the Rotterdam Econometric Institute Reprint series during 1957-2005.

A comprehensive literature classification of simulation optimisation methods

Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measur

A comprehensive literature classification of simulation optimisation methods

Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measur