scholarly journals Two-stage Robust Optimization of Power Cost Minimization Problem in Gunbarrel Natural Gas Networks by Approximate Dynamic Programming

Author(s):  
Yi-Ze Meng ◽  
Ruo-Ran Chen ◽  
Tian-Hu Deng
Author(s):  
Yi-Ze Meng ◽  
Ruo-Ran Chen ◽  
Ke-Ren Zhang ◽  
Tian-Hu Deng

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Bang Wang ◽  
Qiao Kong ◽  
Qiang Yang

The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.


2011 ◽  
Vol 214 (3) ◽  
pp. 501-511 ◽  
Author(s):  
Chan Hou Che ◽  
Weili Huang ◽  
Andrew Lim ◽  
Wenbin Zhu

2012 ◽  
Vol 26 (1-2) ◽  
pp. 249-267 ◽  
Author(s):  
Xiang Li ◽  
Chen-Fu Chien ◽  
Lixing Yang ◽  
Ziyou Gao

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Hao-xiang Chen ◽  
Ying Nan ◽  
Yi Yang

We present a two-stage method for solving the terrain following (TF)/terrain avoidance (TA) path-planning problem for unmanned combat air vehicles (UCAVs). The 1st stage of planning takes an optimization approach for generating a 2D path on a horizontal plane with no collision with the terrain. In the 2nd stage of planning, an optimal control approach is adopted to generate a 3D flyable path for the UCAV that is as close as possible to the terrain. An approximate dynamic programming (ADP) algorithm is used to solve the optimal control problem in the 2nd stage by training an action network to approximate the optimal solution and training a critical network to approximate the value function. Numerical simulations indicate that ADP can determine the optimal control variables for UCAVs; relative to the conventional optimization method, the optimal control approach with ADP shows a better performance under the same conditions.


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