scholarly journals The Chemical Reaction Optimization Approach to Solving the Environmentally Sustainable Network Design Problem

2013 ◽  
Vol 29 (2) ◽  
pp. 140-158 ◽  
Author(s):  
W. Y. Szeto ◽  
Yi Wang ◽  
S. C. Wong
Keyword(s):  
Network Design ◽  
Chemical Reaction ◽  
Design Problem ◽  
Network Design Problem ◽  
Optimization Approach ◽  
Chemical Reaction Optimization ◽  
Environmentally Sustainable ◽  
Reaction Optimization

Chaotic Chemical Reaction Optimization Approach to Receding Horizon Control for Multiple UAVs Formation

2015 ◽  
Author(s):  
Zenghu Zhang ◽  
Haibin Duan
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Chemical Reaction ◽  
Optimization Algorithm ◽  
Receding Horizon Control ◽  
Optimization Approach ◽  
Chemical Reaction Optimization ◽  
Receding Horizon ◽  
Aerial Vehicles ◽  
Reaction Optimization ◽  
Chaotic Operator

In this paper, a chaotic chemical reaction optimization approach to receding horizon control is proposed for multiple unmanned aerial vehicles formation. To keep the coordinated formation with the minimum cost value in all of the planning horizons, the unmanned aerial vehicles formation problem is converted to online optimization problems by giving a receding horizon control scheme. The chemical reaction optimization algorithm is a new optimization inspired by the nature of chemical reactions. Furthermore, the chaotic operator is utilized to help the optimization algorithm avoid of the local optimum and find better optimal parameters. Comparative results show that our proposed method outperforms over traditional particle swarm optimization algorithm.

scholarly journals Dynamic Network Design Problem under Demand Uncertainty: An Adjustable Robust Optimization Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Hua Sun ◽  
Ziyou Gao ◽  
Fangxia Zhao
Keyword(s):  
Linear Programming ◽  
Robust Optimization ◽  
Network Design ◽  
Design Problem ◽  
Demand Uncertainty ◽  
Network Design Problem ◽  
Transmission Model ◽  
Optimization Approach ◽  
Robust Network Design ◽  
Adjustable Robust Optimization

This paper develops an adjustable robust optimization approach for a network design problem explicitly incorporating traffic dynamics and demand uncertainty. In particular, a cell transmission model based network design problem of linear programming type is considered to describe dynamic traffic flows, and a polyhedral uncertainty set is used to characterize the demand uncertainty. The major contribution of this paper is to formulate such an adjustable robust network design problem as a tractable linear programming model and justify the model which is less conservative by comparing its solution performance with the robust solution from the usual robust model. The numerical results using one network from the literature demonstrate the modeling advantage of the adjustable robust optimization and provided strategic managerial insights for enacting capacity expansion policies under demand uncertainty.

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