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

2022 ◽  
Author(s):  
Yi-Ze Meng ◽  
Ruo-Ran Chen ◽  
Tian-Hu Deng
Keyword(s):  
Dynamic Programming ◽  
Natural Gas ◽  
Robust Optimization ◽  
Minimization Problem ◽  
Approximate Dynamic Programming ◽  
Cost Minimization ◽  
Two Stage ◽  
Power Cost ◽  
Gas Networks ◽  
Cost Minimization Problem

scholarly journals Two-stage Robust Power Cost Minimization in a Natural Gas Compressor Station

2021 ◽  
Author(s):  
Yi-Ze Meng ◽  
Ruo-Ran Chen ◽  
Ke-Ren Zhang ◽  
Tian-Hu Deng
Keyword(s):  
Natural Gas ◽  
Cost Minimization ◽  
Compressor Station ◽  
Two Stage ◽  
Power Cost

scholarly journals Energy Cost Minimization in Heterogeneous Cellular Networks with Hybrid Energy Supplies

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Bang Wang ◽  
Qiao Kong ◽  
Qiang Yang
Keyword(s):  
Energy Consumption ◽  
Cellular Networks ◽  
Minimization Problem ◽  
Energy Cost ◽  
Cost Minimization ◽  
Energy Allocation ◽  
Green Energy ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Cost Minimization Problem

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.

The multiple container loading cost minimization problem

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

The train fueling cost minimization problem with fuzzy fuel prices

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

scholarly journals A Two-Stage Method for UCAV TF/TA Path Planning Based on Approximate Dynamic Programming

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Hao-xiang Chen ◽  
Ying Nan ◽  
Yi Yang
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Path Planning ◽  
Approximate Dynamic Programming ◽  
Optimal Solution ◽  
Planning Problem ◽  
Optimization Approach ◽  
Two Stage ◽  
Control Approach ◽  
Optimal Control Approach

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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