Preferences for Prevention: People Assume Expensive Problems Have Expensive Solutions

Risk Analysis ◽  
2021 ◽  
Author(s):  
Talbot M. Andrews ◽  
John Barry Ryan
Keyword(s):  
Expensive Problems

scholarly journals Sensitivity Analysis for Microscopic Crowd Simulation

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 162
Author(s):  
Marion Gödel ◽  
Rainer Fischer ◽  
Gerta Köster
Keyword(s):  
Sensitivity Analysis ◽  
Low Cost ◽  
Input Parameter ◽  
Dimensional Subspace ◽  
Crowd Simulation ◽  
Pedestrian Dynamics ◽  
Sensitivity Indices ◽  
Expensive Problems ◽  
Influential Parameters ◽  
Typical Scenario

Microscopic crowd simulation can help to enhance the safety of pedestrians in situations that range from museum visits to music festivals. To obtain a useful prediction, the input parameters must be chosen carefully. In many cases, a lack of knowledge or limited measurement accuracy add uncertainty to the input. In addition, for meaningful parameter studies, we first need to identify the most influential parameters of our parametric computer models. The field of uncertainty quantification offers standardized and fully automatized methods that we believe to be beneficial for pedestrian dynamics. In addition, many methods come at a comparatively low cost, even for computationally expensive problems. This allows for their application to larger scenarios. We aim to identify and adapt fitting methods to microscopic crowd simulation in order to explore their potential in pedestrian dynamics. In this work, we first perform a variance-based sensitivity analysis using Sobol’ indices and then crosscheck the results by a derivative-based measure, the activity scores. We apply both methods to a typical scenario in crowd simulation, a bottleneck. Because constrictions can lead to high crowd densities and delays in evacuations, several experiments and simulation studies have been conducted for this setting. We show qualitative agreement between the results of both methods. Additionally, we identify a one-dimensional subspace in the input parameter space and discuss its impact on the simulation. Moreover, we analyze and interpret the sensitivity indices with respect to the bottleneck scenario.

scholarly journals Evolutionary Optimization of High-Dimensional Multiobjective and Many-Objective Expensive Problems Assisted by a Dropout Neural Network

2021 ◽  
pp. 1-14
Author(s):  
Dan Guo ◽  
Xilu Wang ◽  
Kailai Gao ◽  
Yaochu Jin ◽  
Jinliang Ding ◽  
...  
Keyword(s):  
Neural Network ◽  
Evolutionary Optimization ◽  
High Dimensional ◽  
Expensive Problems

Similarity- and reliability-assisted fitness estimation for particle swarm optimization of expensive problems

2014 ◽  
Author(s):  
Tong Liu ◽  
Chaoli Sun ◽  
Jianchao Zeng ◽  
Songdong Xue ◽  
Yaochu Jin
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Expensive Problems

Computationally Expensive Problems in Investment Banking

2018 ◽  
pp. 3-24
Author(s):  
Jonathan Rosen ◽  
Christian Kahl ◽  
Russell Goyder ◽  
Mark Gibbs
Keyword(s):  
Investment Banking ◽  
Expensive Problems ◽  
Computationally Expensive

Evaluation of ozonation and cryptic growth for biosolids management in wastewater treatment

1999 ◽  
Vol 39 (10-11) ◽  
pp. 155-158 ◽  
Author(s):  
E. Egemen ◽  
J. Corpening ◽  
J. Padilla ◽  
R. Brennan ◽  
N. Nirmalakhandan
Keyword(s):  
Activated Sludge ◽  
Continuous Flow ◽  
Growth Conditions ◽  
Aeration Tank ◽  
Biomass Growth ◽  
Waste Sludge ◽  
Process Configuration ◽  
Activated Sludge System ◽  
Expensive Problems ◽  
Cryptic Growth

The ultimate disposal of biosolids has been and continues to be one of the most expensive problems faced by wastewater utilities. The objective of this research is to develop a process configuration for reducing the waste sludge generation in an activated sludge plant by promoting cryptic growth conditions (i.e., biomass growth on intracellular products). For this purpose, excess biosolids from a continuous flow activated sludge system were solubilized using ozone as the cell lysis agent, and then returned to the aeration tank. It is hypothesized that growth under such cryptic conditions will result in low net microbial yields, and hence, minimal net solids wastage. The results of these preliminary studies indicate that the proposed process configuration has the potential to reduce the waste sludge production by 40% to 60%.

scholarly journals Multiple infill criterion-assisted hybrid evolutionary optimization for medium-dimensional computationally expensive problems

2021 ◽  
Author(s):  
Shufen Qin ◽  
Chan Li ◽  
Chaoli Sun ◽  
Guochen Zhang ◽  
Xiaobo Li
Keyword(s):  
Evolutionary Algorithms ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Global Search ◽  
Model Management ◽  
The Other ◽  
Local Searches ◽  
Fitness Value ◽  
Expensive Problems ◽  
Computationally Expensive

AbstractSurrogate-assisted evolutionary algorithms have been paid more and more attention to solve computationally expensive problems. However, model management still plays a significant importance in searching for the optimal solution. In this paper, a new method is proposed to measure the approximation uncertainty, in which the differences between the solution and its neighbour samples in the decision space, and the ruggedness of the objective space in its neighborhood are both considered. The proposed approximation uncertainty will be utilized in the surrogate-assisted global search to find a solution for exact objective evaluation to improve the exploration capability of the global search. On the other hand, the approximated fitness value is adopted as the infill criterion for the surrogate-assisted local search, which is utilized to improve the exploitation capability to find a solution close to the real optimal solution as much as possible. The surrogate-assisted global and local searches are conducted in sequence at each generation to balance the exploration and exploitation capabilities of the method. The performance of the proposed method is evaluated on seven benchmark problems with 10, 20, 30 and 50 dimensions, and one real-world application with 30 and 50 dimensions. The experimental results show that the proposed method is efficient for solving the low- and medium-dimensional expensive optimization problems by compared to the other six state-of-the-art surrogate-assisted evolutionary algorithms.

A hybrid meta-model based global optimization method for expensive problems

2019 ◽  
Vol 136 ◽  
pp. 421-428
Author(s):  
Jichao Gu ◽  
Wenqi Li ◽  
Yongzhou Cai
Keyword(s):  
Global Optimization ◽  
Optimization Method ◽  
Global Optimization Method ◽  
Meta Model ◽  
Model Based ◽  
Expensive Problems
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