The model is inspired by the stochastic Kuramoto鈥揤icsek system and belongs to the class of Consensus-Based Optimization methods. In fact, particles move on the hypersurface driven by a drift towards an instantaneous consensus point, computed as a convex combination of the particle locations ...
We introduce a new consensus-based optimization (CBO) method where an interacting particle system is driven by jump-diffusion stochastic differential equations (SDEs). We study well-posedness of th...
Consensus-based optimization (CBO) is a versatile multi-particle optimization method for performing nonconvex and nonsmooth global optimizations in high dimensions. Proofs of global convergence in probability have been achieved for a broad class of objective functions in unconstrained optimizations. In this...
Distributed consensus optimization (DCO) is a common problem definition for optimization problems in networked systems. In DCO, there is a local objective function for each node, and the systematic objective function, i.e. global objective function, is the sum of all local objective functions. DCO...
Consensus-Based Distributed Particle Swarm Optimization with Event-Triggered Communication 来自 Semantic Scholar 喜欢 0 阅读量: 34 作者: ISHIKAWA, Kazuyuki,HAYASHI, Naoki,TAKAI, Shigemasa 摘要: In recent years, there has been considerable interest in Camera Sensor Networks (CSNs) as the next-...
Allowing the integration of renewable energy resources, active customer participation to enable better energy conservation, secure communication to protect from cyber-attacks, and the optimization of the energy-supplying strategy and energy flow to lower and reduce losses are the basic requirements of ...
Intelligent optimization algorithm in nature is originated from the heuristic algorithm, which uses modern intelligent optimization algorithm to optimize the task planning for achieving the balance between the shortest solution time and the optimal solution. Its implementation is generally simple, and the ...
The robust optimization method has progressively become a research hot spot as a valuable means for dealing with parameter uncertainty in optimization problems. Based on the asymmetric cost consensus model, this paper considers the uncertainties of the experts' unit adjustment costs under the background...
In this paper we study large-scale optimization problems in multi-view geometry, in particular the Bundle Adjustment problem. In its conventional formulation, the complexity of existing solvers scale poorly with problem size, hence this component of the Structure-from-Motion pipeline can quickly become...
The emergence of networked systems in various fields brings many complex distributed optimization problems, where multiple agents in the system need to opt... TY Chen,WN Chen,XQ Guo,... - 《IEEE Transactions on Systems Man & Cybernetics Systems》 被引量: 0发表: 0年 Phylogeny of the Platyhel...