Search results for " optimization"
showing 10 items of 2367 documents
Multi-level optimization of a fiber transmission system via nonlinearity management
2006
Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.
Energy-Efficient Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT
2020
Edge computing provides a promising paradigm to support the implementation of industrial Internet of Things (IIoT) by offloading computational-intensive tasks from resource-limited machine-type devices (MTDs) to powerful edge servers. However, the performance gain of edge computing may be severely compromised due to limited spectrum resources, capacity-constrained batteries, and context unawareness. In this chapter, we consider the optimization of channel selection which is critical for efficient and reliable task delivery. We aim at maximizing the long-term throughput subject to long-term constraints of energy budget and service reliability. We propose a learning-based channel selection fr…
Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery
2016
This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…
Energy-Efficient M2M Communications in for Industrial Automation
2020
M2M communication with autonomous data acquisition and exchange plays a key role in realizing the “control”-oriented tactile Internet (TI) applications such as industrial automation. In this chapter, we develop a two-stage access control and resource allocation algorithm. In the first stage, we introduce a contract-based incentive mechanism to motivate some delay-tolerant machine-type communication (MTC) devices to postpone their access demands in exchange for higher access opportunities. In the second stage, a long-term cross-layer online resource allocation approach is based on Lyapunov optimization, which jointly optimizes rate control, power allocation, and channel selection without pri…
Optimizing Renewable Power Management in Transmission Congestion. An Energy Hub Model Using Hydrogen Storage
2021
Energy production from distributed renewable power plants underwent a takeoff in last years as never before. Nevertheless, the installation of technologies based on variable energy resources and their connection on transmission power lines might cause congestions due to the transmission capacity limits. This paper describes the modelization of a HV transmission line with local renewable production and its optimal management through an Energy Hub model. Aim of the study is to identify the optimal size of the power storage, based on an electoryzer, a hydrogen storage and a fuel cell, in order to minimize the congestion risks and to maximize the exploitation of renewable energy production.
Periodic Variance Maximization using Generalized Eigenvalue Decomposition applied to Remote Photoplethysmography estimation
2018
International audience; A generic periodic variance maximization algorithm to extract periodic or quasi-periodic signals of unknown periods embedded into multi-channel temporal signal recordings is described in this paper. The algorithm combines the notion of maximizing a periodicity metric combined with the global optimization scheme to estimate the source periodic signal of an unknown period. The periodicity maximization is performed using Generalized Eigenvalue Decomposition (GEVD) and the global optimization is performed using tabu search. A case study of remote photoplethysmography signal estimation has been utilized to assess the performance of the method using videos from public data…
Application of model quality evaluation to systems biology
2008
Application of model quality evaluation to the quasispecies models is presented. These models are useful for the analysis of the DNA and RNA evolution and for the description of the population dynamics of viruses and bacteria. An estimate of the parameters together with their interval of variability is computed and the quality evaluation is tested on the basis of the model prediction error capability.
Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods
2018
Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively direct the solution process. However, when analyzing the performance of these methods, a critical issue is how to systematically involve decision makers. A recent approach to this problem is to replace a decision maker with an artificial one to be able to systematically evaluate and compare reference point based interactive methods in controlled experiments. In this study, a new artificial decision maker is proposed, which reuses the dynamics of particle swarm optimization f…
An efficient swap algorithm for the lattice Boltzmann method
2007
During the last decade, the lattice-Boltzmann method (LBM) as a valuable tool in computational fluid dynamics has been increasingly acknowledged. The widespread application of LBM is partly due to the simplicity of its coding. The most well-known algorithms for the implementation of the standard lattice-Boltzmann equation (LBE) are the two-lattice and two-step algorithms. However, implementations of the two-lattice or the two-step algorithm suffer from high memory consumption or poor computational performance, respectively. Ultimately, the computing resources available decide which of the two disadvantages is more critical. Here we introduce a new algorithm, called the swap algorithm, for t…
A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows
2009
This paper presents an efficient and well-scalable metaheuristic for fleet size and mix vehicle routing with time windows. The suggested solution method combines the strengths of well-known threshold accepting and guided local search metaheuristics to guide a set of four local search heuristics. The computational tests were done using the benchmarks of [Liu, F.-H., & Shen, S.-Y. (1999). The fleet size and mix vehicle routing problem with time windows. Journal of the Operational Research Society, 50(7), 721-732] and 600 new benchmark problems suggested in this paper. The results indicate that the suggested method is competitive and scales almost linearly up to instances with 1000 custome…