The development of a novel multi-objective optimization framework for non-vertical well placement based on a modified non-dominated sorting genetic algorithm-II

2019 ◽  
Vol 23 (5) ◽  
pp. 1065-1085 ◽  
Author(s):  
Auref Rostamian ◽  
Saeid Jamshidi ◽  
Emily Zirbes
Keyword(s):  
Genetic Algorithm ◽  
Multi Objective Optimization ◽  
Well Placement ◽  
Vertical Well ◽  
Multi Objective ◽  
Optimization Framework

Multi-Objective Optimization of Slope Stability Using Wedge Analysis and Genetic Algorithm

2018 ◽  
pp. 221-239
Author(s):  
Sarat Kumar Das
Keyword(s):  
Genetic Algorithm ◽  
Slope Stability ◽  
Slope Angle ◽  
Seismic Zone ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Waste Containment ◽  
Multi Objective ◽  
Optimization Framework ◽  
Waste Containment Systems

Slope stability of different waste containment systems is a matter of serious concern due to its impact on air, land, and water pollution, affecting human and aquatic lives. It has been observed that most of the waste containment slope failures are translational failure. In this chapter, the slope stability analysis of the waste containment is discussed with translational failure (wedge analysis) in single and multi-objective optimization framework using genetic algorithm (GA). Non-dominated sorting genetic algorithm II (NSGA-II) is found to efficient in developing the Pareto front in terms of factor of safety (FOS), height of embankment, and volume of the failed slope. The FOS decreased with increase in height of the slope and the volume of the slope also increased. The optimized slope in terms of different slope angle and with seismic coefficients is also discussed. Such a study will help the professional in deciding the height of the slope as per the FOS in a specified seismic zone.

MULTI-OBJECTIVE OPTIMIZATION OF OFFSHORE TSUNAMI OBSERVATION POINTS BY GENETIC ALGORITHM

2020 ◽  
Vol 76 (2) ◽  
pp. I_325-I_330
Author(s):  
Kazutoshi KURAMOTO ◽  
Fumiyasu MAKINOSHIMA ◽  
Anawat SUPPASRI ◽  
Fumihiko IMAMURA
Keyword(s):  
Genetic Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

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