Learning-aided evolution for optimization

ZH Zhan, JY Li, S Kwong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Learning and optimization are the two essential abilities of human beings for problem
solving. Similarly, computer scientists have made great efforts to design artificial neural …

Multiobjective multifactorial optimization in evolutionary multitasking

A Gupta, YS Ong, L Feng… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
In recent decades, the field of multiobjective optimization has attracted considerable interest
among evolutionary computation researchers. One of the main features that makes …

A new decomposition-based NSGA-II for many-objective optimization

M Elarbi, S Bechikh, A Gupta, LB Said… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Multiobjective evolutionary algorithms (MOEAs) have proven their effectiveness and
efficiency in solving problems with two or three objectives. However, recent studies show …

TTSA: An effective scheduling approach for delay bounded tasks in hybrid clouds

H Yuan, J Bi, W Tan, MC Zhou… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
The economy of scale provided by cloud attracts a growing number of organizations and
industrial companies to deploy their applications in cloud data centers (CDCs) and to …

Dynamic multi-objective optimization using evolutionary algorithms: a survey

R Azzouz, S Bechikh, L Ben Said - Recent advances in evolutionary multi …, 2016 - Springer
Abstract Dynamic Multi-objective Optimization is a challenging research topic since the
objective functions, constraints, and problem parameters may change over time. Although …

Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network

DG Mogale, M Kumar, SK Kumar, MK Tiwari - Transportation Research Part …, 2018 - Elsevier
In the last few decades, production and procurement of food grain in India have steadily
increased, however, storage capacity has not increased proportionally. The government of …

Cost and makespan scheduling of workflows in clouds using list multiobjective optimization technique

P Han, C Du, J Chen, F Ling, X Du - Journal of Systems Architecture, 2021 - Elsevier
Highly scalable resource supply capacity of cloud computing has greatly improved the
execution speed of workflow applications, however, traditional workflow scheduling …

CG-CFPANet: A multi-task network for built-up area extraction from SDGSAT-1 and Sentinel-2 remote sensing images

L Wang, C Ye, F Chen, N Wang, C Li… - … Journal of Digital …, 2024 - Taylor & Francis
Accurate extraction of built-up areas is helpful to urban development and map updating.
Nighttime light (NTL) data can capture the lighting signal of ground objects. However, most …

Bulk wheat transportation and storage problem of public distribution system

DG Mogale, SK Kumar, FPG Márquez… - Computers & Industrial …, 2017 - Elsevier
This research investigates the multi-period multi-modal bulk wheat transportation and
storage problem in a two-stage supply chain network of Public Distribution System (PDS) …

Many-objective optimization using evolutionary algorithms: A survey

S Bechikh, M Elarbi, L Ben Said - Recent advances in evolutionary multi …, 2017 - Springer
Abstract Multi-objective Evolutionary Algorithms (MOEAs) have proven their effectiveness
and efficiency in solving complex problems with two or three objectives. However, recent …