Skip to main content

Various optimization algorithms for teaching and research

Project description

biogeme-optimization

PyPi

Various optimization algorithms used for teaching and research

The package contains the following modules:

teaching

It contains various functions and classes to teach optimization.

algebra

It contains functions dealing with linear algebra:

  • A modified Cholesky factorization introduced by Schnabel and Eskow (1999)
  • The calculation of a descent direction based on this factorization.

bfgs

The functions in this module calculate

  • the BFGS update of the hessian approximation (see Eq. (13.12) in Bierlaire (2015)),
  • the inverse BFGS update of the hessian approximation (see Eq. (13.13) in Bierlaire (2015)).

bounds

This module mainly defines the class Boundsthat manages the bound constraints.

diagnostics

This module defines the diagnostic of some optimization subproblems (dogleg, and comjugate gradient).

exceptions

It defines the OptimizationError exception.

format

It defines the class FormattedColumns that formats the information reported at each iteration of an algorithm.

function

It defines the abstract class FunctionToMinimize that encapsulate the calculation of the objective function and its derivatives.

hybrid_function

It defines the class HybridFunction that calculates the objective function and its derivatives, where the second derivative can be either the analytical hessian, or a BFGS approximation.

linesearch

This module implements the line search algorithms (see Chapter 11 in Bierlaire, 2015).

simple_bounds

This module implements the minimization algorithm under bound constraints proposed by Conn et al. (1988).

trust_region

This module implements the trust region algorithms (see Chapter 12 in Bierlaire, 2015).

References

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

biogeme-optimization-0.0.6a0.tar.gz (68.4 kB view details)

Uploaded Source

Built Distribution

biogeme_optimization-0.0.6a0-py3-none-any.whl (65.4 kB view details)

Uploaded Python 3

File details

Details for the file biogeme-optimization-0.0.6a0.tar.gz.

File metadata

File hashes

Hashes for biogeme-optimization-0.0.6a0.tar.gz
Algorithm Hash digest
SHA256 178543c0d5fa70f681a4eddab7ee5f0d2e74ea9cdc116a6c27b02e55fe70c7e1
MD5 56944a09ab3576e76cd8beac92823996
BLAKE2b-256 d3d92f624c6838e5bf5ae53741b7bbf9611274fdb7c4eb2a7ce0b4fe4bef86cf

See more details on using hashes here.

File details

Details for the file biogeme_optimization-0.0.6a0-py3-none-any.whl.

File metadata

File hashes

Hashes for biogeme_optimization-0.0.6a0-py3-none-any.whl
Algorithm Hash digest
SHA256 b80db0489af85dbd5c0db4ac0fd31ac98f87c6e848ba1fb766bb78e8a196540c
MD5 c7120b9292ff674b20c712800b6ce5a2
BLAKE2b-256 0b8ddff97b17ffedfab65fe4109b18666630e9e3dc4018e6df7cb1f677ca67a4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page