Distributed Online Convex Programming for Collision Avoidance in Multi-agent Autonomous Vehicle Systemsdoi:10.23919/ACC.2019.8814857Guohui DingHadi RavanbakhshZhiyuan LiuSriram SankaranarayananLijun ChenIEEEAdvances in Computing and Communications
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Online ISSN 1573-2894 Publisher Kluwer Academic Publishers Additional Links Register for Journal Updates Editorial Board About This Journal Manuscript Submission Topics Convex and Discrete Geometry Optimization Operations Research, Mathematical Programming Statistics, general Operation Research/Decision ...
Convex Analysis and Nonlinear Optimization: Theory and Examples (2006) View more references Cited by (1) Convex Hull Pricing for Unit Commitment: Survey, Insights, and Discussions 2024, Energies View full text Surrogate-assisted cooperative learning genetic programming for the resource-constrained project...
Gao, “Online energy management strategy of fuel cell hybrid electric vehicles: a fractional-order extremum seeking method,” IEEE Transactions on Industrial Electronics, vol. 65, no. 8, pp. 6787–6799, 2018. Article Google Scholar C. Labar, E. Garone, M. Kinnaert, and C. Ebenbauer, ...
The 2 and energy constraints of flexible resources in distributed EHVPP can be described as a convex polyhedral characterized by a set of inequality constraints, enabling the mapping of the regulation ability to feasible domains, where, , , and represent the correlation parameters with the current ...
As a result, the dual decomposition methods developed for multistage stochastic optimization problems may not be directly applicable for the multistage MPC problem, from an online computation perspective. Keeping this in mind, it may seem that approximate solution now is better than accurate solution ...
In an online convex optimization problem a decision-maker makes a sequence of decisions, i.e., chooses a sequence of points in Euclidean space, from a fixe... E Hazan,A Agarwal,S Kale - 《Machine Learning》 被引量: 938发表: 2007年 Optimal Distributed Online Prediction Using Mini-Batches ...
12 is a nonconvex, nonlinear programming (NLP) problem whose size grows with the number of discrete time steps in T . A large number of time steps may be required to capture the diurnal periodicity of loading conditions as well as leverage the high-resolution frequen- cies of modern ...
The decomposition of the LP solution into a convex combination of integer embeddings for each service ϕ∈Φ may be performed using Algorithm 1, depicted in FIG. 6, where the decomposition of service ϕ is composed of Kϕ embeddings Dϕ={D1ϕ, . . . , DKϕϕ}, where each ...