Multi-objective optimization control method for multi-user multi-service access in heterogeneous wireless networks

2019 ◽  
Vol 34 (7) ◽  
pp. 708-715
Author(s):  
董晓庆 DONG Xiao-qing ◽  
程良伦 CHENG Liang-lun ◽  
陈洪财 CHEN Hong-cai ◽  
郑耿忠 ZHENG Geng-zhong ◽  
谢森林 XIE Sen-lin
Keyword(s):  
Wireless Networks ◽  
Control Method ◽  
Heterogeneous Wireless Networks ◽  
Service Access ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Control

Urban Oversaturated Traffic Network Control Based on Preference Multi-Objective Compatible Optimization Control

2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan
Keyword(s):  
Control Problem ◽  
Control Algorithm ◽  
Control Method ◽  
Network Control ◽  
Feasible Region ◽  
Traffic Network ◽  
Total Delay ◽  
Multi Objective ◽  
Optimization Control ◽  
Objective Control

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

scholarly journals Optimum multi-service access selection over heterogeneous wireless networks

2014 ◽  
Vol 27 (3) ◽  
pp. 328-338
Author(s):  
Johnny Choque ◽  
Luis-Francisco Díez ◽  
Alberto-Eloy García ◽  
Ramón Agüero ◽  
Luis Muñoz
Keyword(s):  
Wireless Networks ◽  
Heterogeneous Wireless Networks ◽  
Service Access ◽  
Access Selection

scholarly journals Freeway Traffic Congestion Reduction and Environment Regulation via Model Predictive Control

Algorithms ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 220 ◽  
Author(s):  
Juan Chen ◽  
Yuxuan Yu ◽  
Qi Guo
Keyword(s):  
Model Predictive Control ◽  
Fuel Consumption ◽  
Predictive Control ◽  
Traffic Congestion ◽  
Control Method ◽  
Optimization Method ◽  
Speed Limit ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

This paper proposes a model predictive control method based on dynamic multi-objective optimization algorithms (MPC_CPDMO-NSGA-II) for reducing freeway congestion and relieving environment impact simultaneously. A new dynamic multi-objective optimization algorithm based on clustering and prediction with NSGA-II (CPDMO-NSGA-II) is proposed. The proposed CPDMO-NSGA-II algorithm is used to realize on-line optimization at each control step in model predictive control. The performance indicators considered in model predictive control consists of total time spent, total travel distance, total emissions and total fuel consumption. Then TOPSIS method is adopted to select an optimal solution from Pareto front obtained from MPC_CPDMO-NSGA-II algorithm and is applied to the VISSIM environment. The control strategies are variable speed limit (VSL) and ramp metering (RM). In order to verify the performance of the proposed algorithm, the proposed algorithm is tested under the simulation environment originated from a real freeway network in Shanghai with one on-ramp. The result is compared with fixed speed limit strategy and single optimization method respectively. Simulation results show that it can effectively alleviate traffic congestion, reduce emissions and fuel consumption, as compared with fixed speed limit strategy and classical model predictive control method based on single optimization method.

Multi-Objective Optimization in 5G Wireless Networks With Massive MIMO

2018 ◽  
Vol 22 (11) ◽  
pp. 2346-2349 ◽  
Author(s):  
Sotirios K. Goudos ◽  
Panagiotis D. Diamantoulakis ◽  
George K. Karagiannidis
Keyword(s):  
Wireless Networks ◽  
Massive Mimo ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals A Multi-Objective Model-Based Vertical Handoff Algorithm for Heterogeneous Wireless Networks

2020 ◽  
Author(s):  
Shumin Wang ◽  
Honggui Deng ◽  
Rujing Xiong ◽  
Gang Liu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Optimization Model ◽  
Heterogeneous Wireless Networks ◽  
Base Station ◽  
Vertical Handoff ◽  
Chain Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Network State ◽  
Blocking Rate ◽  
The Impact

Abstract An optimized algorithm based on multi-objective optimization model is proposed to solve the problem that existing vertical handoff algorithms do not comprehensively consider the impact of users and the network during handoff process. We build Markov chain model of base station to calculate a more accurate network state. Then a multi-objective optimization model is derived to maximize the value of the network state and the user data receiving rate. The multi-objective genetic algorithm NSGA-II is finally employed to turn the model into a final vertical handoffff strategy. The results of the simulation for throughput and blocking rate of networks demonstrate our algorithm significantly increases the system throughput and reduces the blocking rate compared with the existing vertical switching strategy.

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