Search results for "OPTIMIZATION"
showing 10 items of 2824 documents
An Integrated fuzzy Cells-classifier
2006
The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. In this paper a genetic algorithm is proposed to fuse the classification results due to different distance functions. The combination is based on the optimization of a vote strategy and it is applied to cells classification.
On thermoeconomics of energy systems at variable load conditions: integrated optimization of plant design and operation
2007
Abstract Thermoeconomics has been assuming a growing role among the disciplines oriented to the analysis of energy systems, its different methodologies allowing solution of problems in the fields of cost accounting, plant design optimisation and diagnostic of malfunctions. However, the thermoeconomic methodologies as such are particularly appropriate to analyse large industrial systems at steady or quasi-steady operation, but they can be hardly applied to small to medium scale units operating in unsteady conditions to cover a variable energy demand. In this paper, the fundamentals of thermoeconomics for systems operated at variable load are discussed, examining the cost formation process an…
Thermoeconomic optimization of a renewable polygeneration system serving a small isolated community
2015
During the last years, special attention has been paid to renewable polygeneration technologies, able of simultaneously producing thermal, cooling, electrical energy and desalinated water from seawater. This paper focuses on an innovative polygeneration system driven by renewable energy sources, including the following technologies: hybrid photovoltaic/thermal collectors, concentrating parabolic trough (CPVT), a biomass heater, a single-stage absorption chiller and a multiple-effect distillation desalination system. The system is designed to cover the base load of an isolated small community. In previous papers, the dynamic simulation model about plant operation is discussed. In this paper,…
Thermodynamic, Exergy, and Thermoeconomic analysis of Multiple Effect Distillation Processes
2018
Abstract Multiple effect distillation (MED) is nowadays the preferred technology for the construction of new plants based on thermal processes in the growing desalination market. MED technology, in fact, presents a number of advantages with respect to the more traditional multistage flash technology, among all the lower energy consumption achievable in MED plants. However, a large potential for improvement in terms of lowering production costs still exists, which stimulates further efforts on process optimization from companies and researchers involved in the field. Thermodynamic and exergy analysis provides useful insights regarding the identification of main inefficiencies and the margins…
Performance Analysis of a RED-MED Salinity Gradient Heat Engine
2018
A performance analysis of a salinity gradient heat engine (SGP-HE) is presented for the conversion of low temperature heat into power via a closed-loop Reverse Electrodialysis (RED) coupled with Multi-Effect Distillation (MED). Mathematical models for the RED and MED systems have been purposely developed in order to investigate the performance of both processes and have been then coupled to analyze the efficiency of the overall integrated system. The influence of the main operating conditions (i.e., solutions concentration and velocity) has been quantified, looking at the power density and conversion efficiency of the RED unit, MED Specific Thermal Consumption (STC) and at the overall syste…
Fuzzy portfolio optimization under downside risk measures
2007
This paper presents two fuzzy portfolio selection models where the objective is to minimize the downside risk constrained by a given expected return. We assume that the rates of returns on securities are approximated as LR-fuzzy numbers of the same shape, and that the expected return and risk are evaluated by interval-valued means. We establish the relationship between those mean-interval definitions for a given fuzzy portfolio by using suitable ordering relations. Finally, we formulate the portfolio selection problem as a linear program when the returns on the assets are of trapezoidal form.
Contribution to the study of the recovery of wast heat : study and optimization of Stirling engines
2012
Several machines currently used, internal combustion engines for the car industry or thermal power plants in energy, exhaust a considerable amount of heat. Generally this heat is dispersed in the atmosphere and its energy lost. So we took a special interest in external heat engines which primary energy is heat energy, and more particularly in Stirling engines. One of its main characteristics is the used of energy from heat produced externally like energy source. This allows Stirling engines to be multi-fuel and even to use natural heat energy.The study carried out is made up of two parts. First, a three zones zero dimensional finite-time thermodynamic model has been developed. It takes into…
Licensed and Unlicensed Spectrum Management for Energy-Efficient Cognitive M2M
2020
Edge computing has emerged as a promising solution for relieving the tension between resource-limited MTDs and computational-intensive tasks. To realize successful task offloading with limited spectrum, we focus on the cognitive machine-to-machine (CM2M) paradigm which enables a massive number of MTDs to either opportunistically use the licensed spectrum that is temporarily available, or to exploit the under-utilized unlicensed spectrum. We formulate the channel selection problem with both licensed and unlicensed spectrum as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to devel…
Efficiency improvement of DC* through a Genetic Guidance
2017
DC∗ is a method for generating interpretable fuzzy information granules from pre-classified data. It is based on the subsequent application of LVQ1 for data compression and an ad-hoc procedure based on A∗ to represent data with the minimum number of fuzzy information granules satisfying some interpretability constraints. While being efficient in tackling several problems, the A∗ procedure included in DC∗ may happen to require a long computation time because the A∗ algorithm has exponential time complexity in the worst case. In this paper, we approach the problem of driving the search process of A∗ by suggesting a close-to-optimal solution that is produced through a Genetic Algorithm (GA). E…
A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics
2006
We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.