Search Results for author:
Found 15 papers, 3 papers with code
Effective anytime algorithm for multiobjective combinatorial optimization problems
In multiobjective optimization, the result of an optimization algorithm is a set of efficient solutions from which the decision maker selects one.
Using metaheuristics for the location of bicycle stations
In this work, we solve the problem of finding the best locations to place stations for depositing/collecting shared bicycles.
Optimising Communication Overhead in Federated Learning Using NSGA-II
Federated learning is a training paradigm according to which a server-based model is cooperatively trained using local models running on edge devices and ensuring data privacy.
Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga
This article presents the problem of locating electric vehicle (EV) charging stations in a city by defining the Electric Vehicle Charging Stations Locations (EV-CSL) problem.
Reliable and Fast Recurrent Neural Network Architecture Optimization
This article introduces Random Error Sampling-based Neuroevolution (RESN), a novel automatic method to optimize recurrent neural network architectures.
A Fresh Approach to Evaluate Performance in Distributed Parallel Genetic Algorithms
This work proposes a novel approach to evaluate and analyze the behavior of multi-population parallel genetic algorithms (PGAs) when running on a cluster of multi-core processors.
Bayesian Neural Architecture Search using A Training-Free Performance Metric
Recurrent neural networks (RNNs) are a powerful approach for time series prediction.
JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training
Then, volunteers access the web page of the problem and start processing the tasks in their web browsers.
Random Error Sampling-based Recurrent Neural Network Architecture Optimization
Our findings show that we can achieve state-of-the-art error performance and that we reduce by half the time needed to perform the optimization.
CMI: An Online Multi-objective Genetic Autoscaler for Scientific and Engineering Workflows in Cloud Infrastructures with Unreliable Virtual Machines
Cloud Computing is becoming the leading paradigm for executing scientific and engineering workflows.
DLOPT: Deep Learning Optimization Library
Deep learning hyper-parameter optimization is a tough task.
BIN-CT: Urban Waste Collection based in Predicting the Container Fill Level
The objective of the system is the cost reduction of the waste collection service by means of the minimization in distance traveled by any truck to collect a container, hence the fuel consumption.
Low-Cost Recurrent Neural Network Expected Performance Evaluation
In this study, we propose a low computational cost model to evaluate the expected performance of a given architecture based on the distribution of the error of random samples of the weights.
An Experimental Analysis of the Echo State Network Initialization Using the Particle Swarm Optimization
Here, we present an approach to use the PSO for finding some initial hidden-hidden weights of the ESN model.
A Hitchhiker's Guide to Search-Based Software Engineering for Software Product Lines
Search Based Software Engineering (SBSE) is an emerging discipline that focuses on the application of search-based optimization techniques to software engineering problems.
