Bilayer Multi-Objective Optimal Allocation and Sizing of Electric Vehicle Parking Garage

2018 ◽  
Vol 54 (3) ◽  
pp. 1992-2001 ◽  
Author(s):  
Samy Faddel ◽  
Ahmed T. Elsayed ◽  
Osama A. Mohammed
2021 ◽  
Vol 292 ◽  
pp. 126066
Author(s):  
Ridoy Das ◽  
Yue Wang ◽  
Krishna Busawon ◽  
Ghanim Putrus ◽  
Myriam Neaimeh

2014 ◽  
Vol 538 ◽  
pp. 127-133 ◽  
Author(s):  
Zhao Ning Zhang ◽  
Zhong Zhou Hao ◽  
Zheng Gao

To alleviate the conflicts between the current flight traffic demand and the resource constraints of airspace, we need to improve the restrictions of flow allocation caused by the static air traffic flow allocation mode. The author analyzes the optimal allocation problem of dynamic adjusting flight flow and draws the conclusion that the problem should satisfy multiple targets, such as low flight delays, low flight cost and balancing the load of the route. Then consider a variety of limiting factors, such as the capacity of the route, flight planning, emergency situations, etc. Then establish multi-objective programming model of dynamic adjusting flight traffic. The objective function is determined by the flight cost, the flight delays and the value of the load balance. And the value of the load balance was first proposed according to the idea of least squares method. Then solve the model based on linear weighted technique. Finally the numerical result shows that the model can satisfy the multiple objectives and dynamic adjust the flight traffic optimally, that proves the rationality and validity of the model and the algorithm.


This paper aimed to demonstrate a metaheuristic as a solution procedure to schedule a two-machine, identical parts robotic cell under breakdown. The proposed previous model enabled one to determine optimal allocation of operations to the machines and corresponding processing times of each machine. For the proposed mathematical model to minimize cycle time and operational cost, multi-objective particle swarm optimization (MOPSO) algorithm was provided. Through some numerical examples, the optimal solutions were compared with the previous results. MOPSO algorithm could find the solutions for problems embeds up to 50 operations in a rationale time.


Energies ◽  
2017 ◽  
Vol 10 (7) ◽  
pp. 975 ◽  
Author(s):  
Xuerui Ma ◽  
Yong Zhang ◽  
Chengliang Yin ◽  
Shifei Yuan

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