Distributed accelerated primal-dual neurodynamic approaches for resource allocation problem  

作　　者：ZHAO You HE Xing YU JunZhi HUANG TingWen 

机构地区：[1]College of Electronic and Information Engineering,Southwest University,Chongqing 400715,China [2]State Key Laboratory for Turbulence and Complex Systems,Department of Advanced Manufacturing and Robotics,College of Engineering,Peking University,Beijing 100871,China [3]Science Program,Texas A&M University at Qatar,Doha 2387,Qatar

出　　处：《Science China(Technological Sciences)》2023年第12期3639-3650,共12页中国科学（技术科学英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant No.62176218);the Fundamental Research Funds for the Central Universities (Grant No.XDJK2020TY003)。

摘　　要：This paper investigates two distributed accelerated primal-dual neurodynamic approaches over undirected connected graphs for resource allocation problems(RAP)where the objective functions are generally convex.With the help of projection operators,a primal-dual framework,and Nesterov's accelerated method,we first design a distributed accelerated primal-dual projection neurodynamic approach(DAPDP),and its convergence rate of the primal-dual gap is O(1/(t^(2)))by selecting appropriate parameters and initial values.Then,when the local closed convex sets are convex inequalities which have no closed-form solutions of their projection operators,we further propose a distributed accelerated penalty primal-dual neurodynamic approach(DAPPD)on the strength of the penalty method,primal-dual framework,and Nesterov's accelerated method.Based on the above analysis,we prove that DAPPD also has a convergence rate O(1/(t^(2)))of the primal-dual gap.Compared with the distributed dynamical approaches based on the classical primal-dual framework,our proposed distributed accelerated neurodynamic approaches have faster convergence rates.Numerical simulations demonstrate that our proposed neurodynamic approaches are feasible and effective.

关 键 词：accelerated primal-dual neurodynamic approaches RAP projection operators penalty method convergence rate O(1/(t^(2))) 

分 类 号：O224[理学—运筹学与控制论]