Resolution of the vehicular control problem on ramp metering through multi-objective algorithm hybridization

Author(s):  
Javier Maldonado ◽  
Jhon Amaya ◽  
D. Feijoo Colomine
2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan

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.


Author(s):  
Gustavo B. Libotte ◽  
Fran S. Lobato ◽  
Gustavo M. Platt ◽  
Francisco D. Moura Neto

The determination of optimal feeding profile of fed-batch fermentation requires the solution of a singular optimal control problem. The complexity in obtaining the solution to this singular problem is due to the nonlinear dynamics of the system model, the presence of control variables in linear form and the existence of constraints in both the state and control variables. Traditionally, during the optimization process, uncertainties associated with design variables, control parameters and mathematical model are not considered. In this contribution, a systematic methodology to evaluate uncertainties during the resolution of a singular optimal control problem is proposed. This approach consists of the Multi-objective Optimization Differential Evolution algorithm associated with Effective Mean Concept. The proposed methodology is applied to determine the feed substrate concentration in fed-batch penicillin fermentation process. The robust multi- objective singular optimal control problem consists of maximizing the productivity and minimizing the operation total time.


2017 ◽  
Vol 27 ◽  
pp. 937-944
Author(s):  
Tamás Luspay ◽  
Alfréd Csikós ◽  
Tamás Péni ◽  
István Varga ◽  
Balázs Kulcsár

2018 ◽  
Vol 5 (3) ◽  
pp. 213
Author(s):  
Peeyush Vats ◽  
Ajay Pal Singh Rathore ◽  
Gunjan Soni

2015 ◽  
Vol 20 (12) ◽  
pp. 4999-5023 ◽  
Author(s):  
Xiaoliang Ma ◽  
Fang Liu ◽  
Yutao Qi ◽  
Lingling Li ◽  
Licheng Jiao ◽  
...  

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