Search results for " optimization."
showing 10 items of 2333 documents
Recovery of oil with unsaturated fatty acids and polyphenols from chaenomelessinensis (Thouin) Koehne: Process optimization of pilot-scale subcritica…
2017
The potential effects of three modern extraction technologies (cold-pressing, microwaves and subcritical fluids) on the recovery of oil from Chaenomelessinensis (Thouin) Koehne seeds have been evaluated and compared to those of conventional chemical extraction methods (Soxhlet extraction). This oil contains unsaturated fatty acids and polyphenols. Subcritical fluid extraction (SbFE) provided the highest yield—25.79 g oil/100 g dry seeds—of the three methods. Moreover, the fatty acid composition in the oil samples was analysed using gas chromatography–mass spectrometry. This analysis showed that the percentages of monounsaturated (46.61%), and polyunsaturated fatty acids (42.14%), after appl…
Factorial graphical models for dynamic networks
2015
AbstractDynamic network models describe many important scientific processes, from cell biology and epidemiology to sociology and finance. Estimating dynamic networks from noisy time series data is a difficult task since the number of components involved in the system is very large. As a result, the number of parameters to be estimated is typically larger than the number of observations. However, a characteristic of many real life networks is that they are sparse. For example, the molecular structure of genes make interactions with other components a highly-structured and, therefore, a sparse process. Until now, the literature has focused on static networks, which lack specific temporal inte…
Principles of scatter search
2006
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first proposed in the 1970s, based on formulations dating back to the 1960s for combining decision rules and problem constraints. In contrast to other evolutionary methods like genetic algorithms, scatter search is founded on the premise that systematic designs and methods for creating new solutions afford significant benefits beyond those derived from recourse to randomization. It uses strategies for search diversification and intensification that have proved effective in a variety of optimization problems. This paper provides…
Semiparametric stochastic frontier models: A generalized additive model approach
2017
Abstract The choice of the functional form of the frontier into a stochastic frontier model is typically neglected in applications and canonical functions are usually considered. This paper introduces a semiparametric approach for stochastic frontier estimation that extends previous works based on pseudo-likelihood estimators allowing flexibility in model selection and capability of imposing monotonicity and concavity constraints. For these purposes the present work introduces a generalized additive framework that moreover permits to model the influence of contextual/environmental factors to the hypothesized production process by the relative extension given by generalized additive models f…
A Feature Rich Distance-Based Many-Objective Visualisable Test Problem Generator
2019
In optimiser analysis and design it is informative to visualise how a search point/population moves through the design space over time. Visualisable distance-based many-objective optimisation problems have been developed whose design space is in two-dimensions with arbitrarily many objective dimensions. Previous work has shown how disconnected Pareto sets may be formed, how problems can be projected to and from arbitrarily many design dimensions, and how dominance resistant regions of design space may be defined. Most recently, a test suite has been proposed using distances to lines rather than points. However, active use of visualisable problems has been limited. This may be because the ty…
DEMAND Project: Bottom-Up Aggregation of Prosumers in Distribution Networks
2018
The paper explains the concept of the DEMAND project, whose aim is to develop a technical framework for allowing a Bottom-Up aggregation of prosumers connected to the distribution grid. Load and generation aggregation is a very current issue given the great potential that the coordinated management of distributed resources has on power systems operation and design. The novelty in DEMAND is the absence of a physical aggregator and the recourse to a virtual aggregation environment (VAE) for allowing the exchange of information among the prosumers in order to provide a service to the DSO. After a general description of the research project, the paper presents the services that the aggregated c…
An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems
2015
This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…
Tracking of Quantized Signals Based on Online Kernel Regression
2021
Kernel-based approaches have achieved noticeable success as non-parametric regression methods under the framework of stochastic optimization. However, most of the kernel-based methods in the literature are not suitable to track sequentially streamed quantized data samples from dynamic environments. This shortcoming occurs mainly for two reasons: first, their poor versatility in tracking variables that may change unpredictably over time, primarily because of their lack of flexibility when choosing a functional cost that best suits the associated regression problem; second, their indifference to the smoothness of the underlying physical signal generating those samples. This work introduces a …
A Review of Key Performance Indicators for Building Flexibility Quantification to Support the Clean Energy Transition
2021
The transition to a sustainable society and a carbon-neutral economy by 2050 requires extensive deployment of renewable energy sources that, due to the aleatority and non-programmability of most of them, may seriously affect the stability of existing power grids. In this context, buildings are increasingly being seen as a potential source of energy flexibility for the power grid. In literature, key performance indicators, allowing different aspects of the load management, are used to investigate buildings’ energy flexibility. The paper reviews existing indicators developed in the context of theoretical, experimental and numerical studies on flexible buildings, outlining the current status a…
CADWAN – A Control Architecture for Dense Wi-Fi Access Networks
2018
The growing demands of ubiquitous computing are leading towards the densification of wireless access networks. The challenges of high density deployments can be addressed by network- wide centralized control. To this end we propose CADWAN – a Control Architecture for efficient management of Dense Wi-Fi Access Networks. Its main advantages are: flexibility (it supports software- defined wireless networking), scalability (it uses a three-tier optimization framework), and extendibility (it exploits a unified control interface with support for heterogeneous devices). Furthermore, CADWAN is complementary to ongoing developments in IEEE 802.11, especially 802.11ax.