No project description provided
Project description
# RevPy
[](https://travis-ci.org/flix-tech/RevPy)
Collection of some revenue management tools for Python 3.
## Features
- Single leg optimizer (EMSRb)
- Fare transformation for unrestricted fare structures
- EMSRb for unrestricted fare structures (EMSRb-MR)
- A multi-flight recapture method (MFRM) for estimating unconstrained demand from sales transaction data
## TODO
- Leg bid price calculator for networks using deterministic LP method
- Based on this, implementation of DAVN
## Literature
1. Talluri and van Ryzin: "The Theory and Practice of Revenue Management", _Springer_ (2004)
2. Fiig et al.: "Optimization of mixed fare structures: Theory and applications", _Journal of Revenue and Pricing Management_ (2010)
3. Ratliff et al.: "A multi-flight recapture heuristic for estimating unconstrained demand from airline bookings", _Journal of Revenue and Pricing Management_ (2008)
[](https://travis-ci.org/flix-tech/RevPy)
Collection of some revenue management tools for Python 3.
## Features
- Single leg optimizer (EMSRb)
- Fare transformation for unrestricted fare structures
- EMSRb for unrestricted fare structures (EMSRb-MR)
- A multi-flight recapture method (MFRM) for estimating unconstrained demand from sales transaction data
## TODO
- Leg bid price calculator for networks using deterministic LP method
- Based on this, implementation of DAVN
## Literature
1. Talluri and van Ryzin: "The Theory and Practice of Revenue Management", _Springer_ (2004)
2. Fiig et al.: "Optimization of mixed fare structures: Theory and applications", _Journal of Revenue and Pricing Management_ (2010)
3. Ratliff et al.: "A multi-flight recapture heuristic for estimating unconstrained demand from airline bookings", _Journal of Revenue and Pricing Management_ (2008)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
revpy-0.1.1.tar.gz
(8.4 kB
view hashes)