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Learning-aided evolution for optimization
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 …
solving. Similarly, computer scientists have made great efforts to design artificial neural …
Multiobjective multifactorial optimization in evolutionary multitasking
In recent decades, the field of multiobjective optimization has attracted considerable interest
among evolutionary computation researchers. One of the main features that makes …
among evolutionary computation researchers. One of the main features that makes …
A new decomposition-based NSGA-II for many-objective optimization
Multiobjective evolutionary algorithms (MOEAs) have proven their effectiveness and
efficiency in solving problems with two or three objectives. However, recent studies show …
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
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 …
industrial companies to deploy their applications in cloud data centers (CDCs) and to …
Dynamic multi-objective optimization using evolutionary algorithms: a survey
Abstract Dynamic Multi-objective Optimization is a challenging research topic since the
objective functions, constraints, and problem parameters may change over time. Although …
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
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 …
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 …
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 …
Nighttime light (NTL) data can capture the lighting signal of ground objects. However, most …
Bulk wheat transportation and storage problem of public distribution system
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) …
storage problem in a two-stage supply chain network of Public Distribution System (PDS) …
Many-objective optimization using evolutionary algorithms: A survey
Abstract Multi-objective Evolutionary Algorithms (MOEAs) have proven their effectiveness
and efficiency in solving complex problems with two or three objectives. However, recent …
and efficiency in solving complex problems with two or three objectives. However, recent …