scholarly journals A Comparison between Genetic Algorithms and Simulated Annealing for Minimizing Transfer Waiting Time in Transit Systems

2016 ◽  
Vol 8 (3) ◽  
pp. 216-221 ◽  
Author(s):  
Vahid Poorjafari ◽  
Wen Long Yue ◽  
Nicholas Holyoak
Keyword(s):  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Waiting Time ◽  
Transit Systems ◽  
In Transit

Simulation-based vulnerability assessment in transit systems with cascade failures

2021 ◽  
Vol 295 ◽  
pp. 126441
Author(s):  
Hongyu Chen ◽  
Limao Zhang ◽  
Qiong Liu ◽  
Hongtao Wang ◽  
Xiaosong Dai
Keyword(s):  
Vulnerability Assessment ◽  
Transit Systems ◽  
Simulation Based ◽  
In Transit

Extraction of decision rules using genetic algorithms and simulated annealing for prediction of severity of traffic accidents by motorcyclists

2021 ◽  
Author(s):  
Holman Ospina-Mateus ◽  
Leonardo Augusto Quintana Jiménez ◽  
Francisco J. Lopez-Valdes ◽  
Shyrle Berrio Garcia ◽  
Lope H. Barrero ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Traffic Accidents ◽  
Decision Rules

Computing the Medical Image Registration Using Meta-Heuristics

2014 ◽  
Vol 643 ◽  
pp. 237-242 ◽  
Author(s):  
Tahari Abdou El Karim ◽  
Bendakmousse Abdeslam ◽  
Ait Aoudia Samy
Keyword(s):  
Image Processing ◽  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Image Registration ◽  
Cost Function ◽  
Population Genetic ◽  
Medical Image ◽  
Medical Image Registration ◽  
Anatomical Structures

The image registration is a very important task in image processing. In the field of medical imaging, it is used to compare the anatomical structures of two or more images taken at different time to track for example the evolution of a disease. Intensity-based techniques are widely used in the multi-modal registration. To have the best registration, a cost function expressing the similarity between these images is maximized. The registration problem is reduced to the optimization of a cost function. We propose to use neighborhood meta-heuristics (tabu search, simulated annealing) and a meta-heuristic population (genetic algorithms). An evaluation step is necessary to estimate the quality of registration obtained. In this paper we present some results of medical image registration

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