Evolutionary optimization methods for high-dimensional expensive problems: A survey
Evolutionary computation is a rapidly evolving field and the related algorithms have been
successfully used to solve various real-world optimization problems. The past decade has …
successfully used to solve various real-world optimization problems. The past decade has …
Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection
Community is a fundamental and highly desired pattern in a Large-scale Undirected
Network (LUN). Community detection is a vital issue when LUN representation learning is …
Network (LUN). Community detection is a vital issue when LUN representation learning is …
A length-adaptive non-dominated sorting genetic algorithm for Bi-objective high-dimensional feature selection
As a crucial data preprocessing method in data mining, feature selection (FS) can be
regarded as a bi-objective optimization problem that aims to maximize classification …
regarded as a bi-objective optimization problem that aims to maximize classification …
Research progress on intelligent optimization techniques for energy-efficient design of ship hull forms
The design optimization of ship hull form based on hydrodynamics theory and simulation-
based design (SBD) technologies generally considers ship performance and energy …
based design (SBD) technologies generally considers ship performance and energy …
Domain adaptation multitask optimization
Multitask optimization (MTO) is a new optimization paradigm that leverages useful
information contained in multiple tasks to help solve each other. It attracts increasing …
information contained in multiple tasks to help solve each other. It attracts increasing …
Damping-assisted evolutionary swarm intelligence for industrial iot task scheduling in cloud computing
Advancements in the Industrial Internet of Things (IIoT) have yielded massive volumes of
data, taxing the capabilities of cloud computing infrastructure. Allocating limited computing …
data, taxing the capabilities of cloud computing infrastructure. Allocating limited computing …
Electric vehicle routing problem with variable vehicle speed and soft time windows for perishable product delivery
Z Liu, X Zuo, M Zhou, W Guan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This work studies perishable products' distribution using electric commercial vehicles
(ECVs). Extra energy is consumed for refrigeration to keep such products from deteriorating …
(ECVs). Extra energy is consumed for refrigeration to keep such products from deteriorating …
A fast nonnegative autoencoder-based approach to latent feature analysis on high-dimensional and incomplete data
F Bi, T He, X Luo - IEEE Transactions on Services Computing, 2023 - ieeexplore.ieee.org
High-Dimensional and Incomplete (HDI) data are frequently encountered in various Big
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …
Learning-based cuckoo search algorithm to schedule a flexible job shop with sequencing flexibility
CR Lin, ZC Cao, MC Zhou - IEEE Transactions on Cybernetics, 2022 - ieeexplore.ieee.org
This work considers an extended version of flexible job-shop problem from a postprinting or
semiconductor manufacturing environment, which needs a directed acyclic graph rather …
semiconductor manufacturing environment, which needs a directed acyclic graph rather …
Profit-optimized computation offloading with autoencoder-assisted evolution in large-scale mobile-edge computing
Cloud-edge hybrid systems are known to support delay-sensitive applications of
contemporary industrial Internet of Things (IoT). While edge nodes (ENs) provide IoT users …
contemporary industrial Internet of Things (IoT). While edge nodes (ENs) provide IoT users …