Limits of Optimization

  • 0Computational Social Science, ETH Zurich, Stampfenbachstrasse 48, 8006 Zurich, Switzerland.
Minds and Machines +

|

|

Summary

This summary is machine-generated.

Optimization, widely used in quantitative sciences, faces limitations when applied to complex social systems. This paper introduces a framework to understand these limitations for better real-world application.

Area Of Science

  • Quantitative Sciences
  • Social Systems Analysis

Background

  • Optimization is a core concept in mathematics and quantitative sciences, focusing on finding the best solution according to an objective function.
  • The widespread availability of computers has led to the broad application of optimization processes across various societal domains.

Purpose Of The Study

  • To critically examine the applicability of optimization techniques developed for abstract mathematical problems to complex, open social systems.
  • To establish a framework for understanding the limitations of optimization in social contexts.

Main Methods

  • Conceptual analysis of optimization principles.
  • Development of a theoretical framework for evaluating optimization in social systems.

Main Results

  • Identified inherent differences between abstract mathematical objects and complex social systems that challenge direct application of optimization.
  • Highlighted the potential pitfalls of applying 'one-size-fits-all' optimization strategies to diverse social phenomena.

Conclusions

  • Optimization processes successful in mathematics may not be directly transferable to complex social systems.
  • A nuanced framework is necessary to determine the appropriate use and limitations of optimization in social contexts.

Related Concept Videos

Accuracy, limits, and approximation 01:28

448

Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...

Limits to Natural Selection 01:38

31.3K

Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.

For one, natural selection can only act upon existing genetic variation. Hypothetically, red tusks may enhance elephant survival by deterring ivory-seeking poachers. However, if there are no gene variants—or alleles—for red tusks, natural selection cannot...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving 01:29

53

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Difference from Background: Limit of Detection 01:05

6.4K

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

Plotting and Calibrating the Root Locus 01:19

117

Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...

One-Degree-of-Freedom System 01:24

488

In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...