Sanction Effectiveness in Iran: A Network Optimization Approach

Operating unmanned aerial vehicles (UAVs) over inhabited areas requires mitigating the risk to persons on the ground. Because the risk depends upon the flight path, UAV operators need approaches (techniques) that can find low-risk flight paths between the mission’s start and finish points. In some areas, the flight paths with the lowest risk are excessively long and indirect because the least-populated areas are too remote. Thus, UAV operators are concerned about the tradeoff between risk and flight time. Although there exist approaches for assessing the risks associated with UAV operations, existing risk-based path planning approaches have considered other risk measures (besides the risk to persons on the ground) or simplified the risk assessment calculation. This paper presents a risk assessment technique and bi-objective optimization methods to find low-risk and time (flight path) solutions and computational experiments to evaluate the relative performance of the methods (their computation time and solution quality). The methods were a network optimization approach that constructed a graph for the problem and used that to generate initial solutions that were then improved by a local approach and a greedy approach and a fourth method that did not use the network solutions. The approaches that improved the solutions generated by the network optimization step performed better than the optimization approach that did not use the network solutions.

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A neural network optimization approach for automatic NMO correction and velocity estimation

10.1190/1.1826552 ◽

1996 ◽

Author(s):

Carlos Calderón‐Macías ◽

Mrinal K. Sen ◽

Paul L. Stoffa

Keyword(s):

Neural Network ◽

Network Optimization ◽

Velocity Estimation ◽

Optimization Approach ◽

Neural Network Optimization ◽

Nmo Correction

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A Network Optimization Approach to Three-Dimensional Collision-Free Robot Path Planning

15th Design Automation Conference: Volume 2 — Design Optimization ◽

10.1115/detc1989-0088 ◽

1989 ◽

Author(s):

P. K. Jain ◽

S. P. Manoochehri

Keyword(s):

Network Optimization ◽

Dimensional Space ◽

Optimal Path ◽

Three Dimensional ◽

Minimum Cost ◽

Optimization Approach ◽

Graph Structure ◽

Three Dimensional Space ◽

Robot Path ◽

Robot Body

Abstract This paper presents a network optimization approach to the generation of tool tip paths in three-dimensional space for robot manipulators working in the presence of obstacles. The developed algorithm relies on a graph structure enumeration of possible path segments between discrete points inside the workspace. An intelligent heuristic scheme is used to select a small searchspace over which the search for the optimal path is carried out. Paths which are optimal with respect to pre-determined objective functions based on robot kinematic and dynamic solutions are synthesized by applying Dijkstra’s minimum cost algorithm. Collision avoidance is checked for the tool tip as well as for the robot body. The methodology is robot independent and can be applied to any robot whose kinematics and dynamics can be solved. A computer program has been developed to implement this approach for three-axis manipulators. Results of the application of this scheme to some robots in this class are also presented.

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