Electric vehicle scheduling: State of the art, critical challenges, and future research opportunities
Electric vehicles can be perceived as a means to achieve carbon reduction, energy
efficiency, and sustainable development of the transportation industry. Electric vehicle sales …
efficiency, and sustainable development of the transportation industry. Electric vehicle sales …
Recent advances in collaborative scheduling of computing tasks in an edge computing paradigm
In edge computing, edge devices can offload their overloaded computing tasks to an edge
server. This can give full play to an edge server's advantages in computing and storage, and …
server. This can give full play to an edge server's advantages in computing and storage, and …
Disassembly sequence planning: a survey
It is well-recognized that obsolete or discarded products can cause serious environmental
pollution if they are poorly be handled. They contain reusable resource that can be recycled …
pollution if they are poorly be handled. They contain reusable resource that can be recycled …
A machine learning and genetic algorithm-based method for predicting width deviation of hot-rolled strip in steel production systems
Width deviation is an important metric for evaluating the quality of a hot-rolled strip in steel
production systems. This paper considers a width deviation prediction problem and …
production systems. This paper considers a width deviation prediction problem and …
Multiobjective U-shaped disassembly line balancing problem considering human fatigue index and an efficient solution
The progress of science and technology speeds up the replacement of products and
produces a large number of end-of-life products. Traditional incineration causes a waste of …
produces a large number of end-of-life products. Traditional incineration causes a waste of …
Highly-accurate community detection via pointwise mutual information-incorporated symmetric non-negative matrix factorization
Community detection, aiming at determining correct affiliation of each node in a network, is a
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …
Surrogate-assisted autoencoder-embedded evolutionary optimization algorithm to solve high-dimensional expensive problems
Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve
computationally expensive problems with some success. However, traditional EAs are not …
computationally expensive problems with some success. However, traditional EAs are not …
MO4: A many-objective evolutionary algorithm for protein structure prediction
Protein structure prediction (PSP) problems are a major biocomputing challenge, owing to
its scientific intrinsic that assists researchers to understand the relationship between amino …
its scientific intrinsic that assists researchers to understand the relationship between amino …
Performance and cost-efficient spark job scheduling based on deep reinforcement learning in cloud computing environments
Big data frameworks such as Spark and Hadoop are widely adopted to run analytics jobs in
both research and industry. Cloud offers affordable compute resources which are easier to …
both research and industry. Cloud offers affordable compute resources which are easier to …
Human–robot collaborative disassembly line balancing problem with stochastic operation time and a solution via multi-objective shuffled frog lea** algorithm
Product disassembly is critically important in recycling end-of-life products, reducing their
negative impact on environmental pollution and minimizing resource waste. Disassembly …
negative impact on environmental pollution and minimizing resource waste. Disassembly …