scholarly journals A Bregman Forward-Backward Linesearch Algorithm for Nonconvex Composite Optimization: Superlinear Convergence to Nonisolated Local Minima

2021 ◽  
Vol 31 (1) ◽  
pp. 653-685
Author(s):  
Masoud Ahookhosh ◽  
Andreas Themelis ◽  
Panagiotis Patrinos
Keyword(s):  
Superlinear Convergence ◽  
Local Minima ◽  
Composite Optimization

Gas-Phase Clustering of NO+ with H2S and H2O

2007 ◽  
Vol 72 (8) ◽  
pp. 1122-1138 ◽  
Author(s):  
Milan Uhlár ◽  
Ivan Černušák
Keyword(s):  
Hydrogen Bonds ◽  
Water Molecule ◽  
Gas Phase ◽  
Saddle Points ◽  
Solvent Molecule ◽  
Local Minima ◽  
Additional Water ◽  
Three Body ◽  
Rain Formation ◽  
Stable Structures

The complex NO+·H2S, which is assumed to be an intermediate in acid rain formation, exhibits thermodynamic stability of ∆Hº300 = -76 kJ mol-1, or ∆Gº300 = -47 kJ mol-1. Its further transformation via H-transfer is associated with rather high barriers. One of the conceivable routes to lower the energy of the transition state is the action of additional solvent molecule(s) that can mediate proton transfer. We have studied several NO+·H2S structures with one or two additional water molecule(s) and have found stable structures (local minima), intermediates and saddle points for the three-body NO+·H2S·H2O and four-body NO+·H2S·(H2O)2 clusters. The hydrogen bonds network in the four-body cluster plays a crucial role in its conversion to thionitrous acid.

scholarly journals Incorporation of Potential Fields and Motion Primitives for the Collision Avoidance of Unmanned Aircraft

2021 ◽  
Vol 11 (7) ◽  
pp. 3103
Author(s):  
Kyuman Lee ◽  
Daegyun Choi ◽  
Donghoon Kim
Keyword(s):  
Collision Avoidance ◽  
Search Algorithm ◽  
Unmanned Aircraft ◽  
Artificial Potential Field ◽  
Tree Search ◽  
Local Minima ◽  
Collision Risk ◽  
Motion Primitives ◽  
Multiple Uavs ◽  
Tree Search Algorithm

Collision avoidance (CA) using the artificial potential field (APF) usually faces several known issues such as local minima and dynamically infeasible problems, so unmanned aerial vehicles’ (UAVs) paths planned based on the APF are safe only in a certain environment. This research proposes a CA approach that combines the APF and motion primitives (MPs) to tackle the known problems associated with the APF. Since MPs solve for a locally optimal trajectory with respect to allocated time, the trajectory obtained by the MPs is verified as dynamically feasible. When a collision checker based on the k-d tree search algorithm detects collision risk on extracted sample points from the planned trajectory, generating re-planned path candidates to avoid obstacles is performed. After rejecting unsafe route candidates, one applies the APF to select the best route among the remaining safe-path candidates. To validate the proposed approach, we simulated two meaningful scenario cases—the presence of static obstacles situation with local minima and dynamic environments with multiple UAVs present. The simulation results show that the proposed approach provides smooth, efficient, and dynamically feasible pathing compared to the APF.

Deterministic and probabilistic occupancy detection with a novel heuristic optimization and Back-Propagation (BP) based algorithm

2021 ◽  
pp. 1-13
Author(s):  
Nuzhat Fatema ◽  
Saeid Gholami Farkoush ◽  
Mashhood Hasan ◽  
H Malik
Keyword(s):  
Convergence Rate ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Hybrid Approach ◽  
Experimental Studies ◽  
Back Propagation ◽  
Heuristic Optimization ◽  
Local Minima ◽  
Occupancy Detection ◽  
Trapping Problem

In this paper, a novel hybrid approach for deterministic and probabilistic occupancy detection is proposed with a novel heuristic optimization and Back-Propagation (BP) based algorithms. Generally, PB based neural network (BPNN) suffers with the optimal value of weight, bias, trapping problem in local minima and sluggish convergence rate. In this paper, the GSA (Gravitational Search Algorithm) is implemented as a new training technique for BPNN is order to enhance the performance of the BPNN algorithm by decreasing the problem of trapping in local minima, enhance the convergence rate and optimize the weight and bias value to reduce the overall error. The experimental results of BPNN with and without GSA are demonstrated and presented for fair comparison and adoptability. The demonstrated results show that BPNNGSA has outperformance for training and testing phase in form of enhancement of processing speed, convergence rate and avoiding the trapping problem of standard BPNN. The whole study is analyzed and demonstrated by using R language open access platform. The proposed approach is validated with different hidden-layer neurons for both experimental studies based on BPNN and BPNNGSA.

Energy absorption of the Kevlar®/PP hybrid composite: fabric to composite optimization

2021 ◽  
pp. 1-9
Author(s):  
Mehrdad Hossein Alizadeh ◽  
Mehdi Kamali Dolatabadi ◽  
Saeed Shaikhzadeh Najar ◽  
Reza Eslami-Farsani
Keyword(s):  
Energy Absorption ◽  
Hybrid Composite ◽  
Composite Optimization
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