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Found 7 papers, 1 papers with code
Distance-aware Attention Reshaping: Enhance Generalization of Neural Solver for Large-scale Vehicle Routing Problems
To address this issue, this paper proposes a distance-aware attention reshaping method, assisting neural solvers in solving large-scale vehicle routing problems.
CEC: Crowdsourcing-based Evolutionary Computation for Distributed Optimization
Inspired by this, this paper intends to introduce crowdsourcing into evolutionary computation (EC) to propose a crowdsourcing-based evolutionary computation (CEC) paradigm for distributed optimization.
A Survey on Distributed Evolutionary Computation
Based on this taxonomy, existing studies on DEC are reviewed in terms of purpose, parallel structure of the algorithm, parallel model for implementation, and the implementation environment.
When Evolutionary Computation Meets Privacy
To this end, in this paper, we discuss three typical optimization paradigms (i. e., \textit{centralized optimization, distributed optimization, and data-driven optimization}) to characterize optimization modes of evolutionary computation and propose BOOM to sort out privacy concerns in evolutionary computation.
Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization
Specifically, PEGA enables users outsourcing COPs to the cloud server holding a competitive GA and approximating the optimal solution in a privacy-preserving manner.
When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System
Specifically, in order to protect privacy, participants locally process sensing data via federated learning and only upload encrypted training models.
Distributed Differential Evolution Based on Adaptive Mergence and Split for Large-Scale Optimization
In this way, the number of subpopulations is adaptively adjusted and better performing subpopulations obtain more individuals.
