Hands-On Data Science with Anaconda by Yuxing Yan

Author:Yuxing Yan
Language: eng
Format: epub
Tags: COM062000 - COMPUTERS / Data Modeling and Design, COM051360 - COMPUTERS / Programming Languages / Python, COM037000 - COMPUTERS / Machine Theory
Publisher: Packt Publishing
Published: 2018-05-31T09:23:30+00:00

Where U() is the utility function and x will be a set of input variables. The following table shows a partial list of applications for optimization:

Area

Name

Description

Economics

Utility function For many variables in the real world, it is difficult to quantify them, such as happiness. For this, economists have developed a utility function. To find an optimal solution, users could maximize their utility function.

Quantity, price, and production A company might consider the best strategy to produce, price, and sell its products.

Welfare transfer Governments might consider many input variables such as incentives to work, crime rate, and other factors.

Optimal tax policy Maximize the GDP growth, subject to controllable inflation rate.

Finance

Portfolio optimization For a given portfolio of expected returns, choose a set of stocks to minimize the portfolio risk.

Optimal investment strategy When facing several possible investment opportunities and many constraints, how to choose the best combination to achieve the best result.

Profit optimization For companies, they want to maximize their profit by optimally choosing their input variables.

High-frequency trading Balance the signalling effect with various bid-and-ask offers, and long-term and short-term profits.

Others

Scheduling Minimize the total cost with certain constraints.

Minimize total cost Consider various trade-offs between certain benefits and costs.

Flying issues Minimize the total distance by visiting certain cities.

Task arrangements With many tasks and potential labor and input variables available, how to achieve an optimal solution.

Application of optimization

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