An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal
MA Dulebenets - Information Sciences, 2021 - Elsevier
Many supply chain stakeholders rely on the cross-docking concept, according to which
products delivered in specific transportation management units to the cross-docking terminal …
products delivered in specific transportation management units to the cross-docking terminal …
Edge–cloud resource scheduling in space–air–ground-integrated networks for internet of vehicles
B Cao, J Zhang, X Liu, Z Sun, W Cao… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The space–air–ground-integrated network (SAGIN) can enhance the performance of the
Internet of Vehicles (IoV). However, the basic hardware differences among communication …
Internet of Vehicles (IoV). However, the basic hardware differences among communication …
Learning to accelerate evolutionary search for large-scale multiobjective optimization
Most existing evolutionary search strategies are not so efficient when directly handling the
decision space of large-scale multiobjective optimization problems (LMOPs). To enhance …
decision space of large-scale multiobjective optimization problems (LMOPs). To enhance …
A survey on learnable evolutionary algorithms for scalable multiobjective optimization
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
A self-adaptive co-evolutionary algorithm for multi-objective flexible job-shop rescheduling problem with multi-phase processing speed selection, condition-based …
Production scheduling and maintenance planning are two interactive factors in modern
manufacturing system. However, at present, almost all studies ignore the impact of …
manufacturing system. However, at present, almost all studies ignore the impact of …
A comprehensive competitive swarm optimizer for large-scale multiobjective optimization
Competitive swarm optimizers (CSOs) have shown very promising search efficiency in large-
scale decision space. However, they face difficulties when solving large-scale multi-/many …
scale decision space. However, they face difficulties when solving large-scale multi-/many …
Evolutionary multitasking for large-scale multiobjective optimization
Evolutionary transfer optimization (ETO) has been becoming a hot research topic in the field
of evolutionary computation, which is based on the fact that knowledge learning and transfer …
of evolutionary computation, which is based on the fact that knowledge learning and transfer …
Many-objective cloud manufacturing service selection and scheduling with an evolutionary algorithm based on adaptive environment selection strategy
T Wang, P Zhang, J Liu, M Zhang - Applied Soft Computing, 2021 - Elsevier
Cloud manufacturing service selection and scheduling (CMSSS) problem has obtained wide
attentions in recent years. However, most existing methods describe this problem as single …
attentions in recent years. However, most existing methods describe this problem as single …
A survey of artificial immune algorithms for multi-objective optimization
Multi-objective immune algorithm (MOIA) is a heuristic algorithm based on artificial immune
system model. Due to its characteristics of antibody clonal selection, automatic antigen …
system model. Due to its characteristics of antibody clonal selection, automatic antigen …
An indicator preselection based evolutionary algorithm with auxiliary angle selection for many-objective optimization
Q Gu, Q Zhou, Q Wang, NN Xiong - Information Sciences, 2023 - Elsevier
Many-objective evolutionary algorithms (MaOEAs) have received significant achievements
in recent years. Maintaining a balance between convergence and diversity becomes a key …
in recent years. Maintaining a balance between convergence and diversity becomes a key …