[HTML][HTML] Artificial neural networks based optimization techniques: A review
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …
using optimization techniques. In this paper, we present an extensive review of artificial …
[HTML][HTML] Evolutionary computation for expensive optimization: A survey
Expensive optimization problem (EOP) widely exists in various significant real-world
applications. However, EOP requires expensive or even unaffordable costs for evaluating …
applications. However, EOP requires expensive or even unaffordable costs for evaluating …
[HTML][HTML] A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
Evolutionary deep learning: A survey
As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …
(DL) has achieved great success in many real-world applications and attracted increasing …
A novel dynamic multiobjective optimization algorithm with non-inductive transfer learning based on multi-strategy adaptive selection
In this article, a novel multi-strategy adaptive selection-based dynamic multiobjective
optimization algorithm (MSAS-DMOA) is proposed, which adopts the non-inductive transfer …
optimization algorithm (MSAS-DMOA) is proposed, which adopts the non-inductive transfer …
Distributed differential evolution with adaptive resource allocation
Distributed differential evolution (DDE) is an efficient paradigm that adopts multiple
populations for cooperatively solving complex optimization problems. However, how to …
populations for cooperatively solving complex optimization problems. However, how to …
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 …
Adaptive distributed differential evolution
Due to the increasing complexity of optimization problems, distributed differential evolution
(DDE) has become a promising approach for global optimization. However, similar to the …
(DDE) has become a promising approach for global optimization. However, similar to the …
Evolutionary computation for intelligent transportation in smart cities: A survey
As the population in cities continues to increase, large-city problems, including traffic
congestion and environmental pollution, have become increasingly serious. The …
congestion and environmental pollution, have become increasingly serious. The …
Dynamic group learning distributed particle swarm optimization for large-scale optimization and its application in cloud workflow scheduling
Cloud workflow scheduling is a significant topic in both commercial and industrial
applications. However, the growing scale of workflow has made such a scheduling problem …
applications. However, the growing scale of workflow has made such a scheduling problem …