multimodal-transportation-optimization | using mathematical programming to solve multi

by hzjken Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | multimodal-transportation-optimization Summary

multimodal-transportation-optimization is a Python library. multimodal-transportation-optimization has no bugs, it has no vulnerabilities and it has low support. However multimodal-transportation-optimization build file is not available. You can download it from GitHub.

In delivery services, many different transportation tools such as trucks, airplanes and ships are available. Different choices of routes and transporation tools will lead to different costs. To minimize cost, we should consider goods consolidation (Occassions when different goods share a journey together.), different transportation costs and delivery time constraints etc. This project uses mathematical programming to model such situation and solves for overall cost minimization solution. The model construction offers options of two mathematical programming frameworks, DOcplex and CVXPY.

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Support

multimodal-transportation-optimization has a low active ecosystem.

It has 167 star(s) with 60 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of multimodal-transportation-optimization is current.

Quality

multimodal-transportation-optimization has 0 bugs and 57 code smells.

Security

multimodal-transportation-optimization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

multimodal-transportation-optimization code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

multimodal-transportation-optimization does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

multimodal-transportation-optimization releases are not available. You will need to build from source code and install.

multimodal-transportation-optimization has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

multimodal-transportation-optimization saves you 115 person hours of effort in developing the same functionality from scratch.

It has 292 lines of code, 10 functions and 1 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed multimodal-transportation-optimization and discovered the below as its top functions. This is intended to give you an instant insight into multimodal-transportation-optimization implemented functionality, and help decide if they suit your requirements.

Build the model
Build the CvX model
Builds the cplex model
Solve the model
Calculates the warehouse cost for a given time
Set the parameters for the route
Prints a txt description
Reads a CSV file and converts it to a DataFrame

Get all kandi verified functions for this library.

multimodal-transportation-optimization Key Features

No Key Features are available at this moment for multimodal-transportation-optimization.

multimodal-transportation-optimization Examples and Code Snippets

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Community Discussions

No Community Discussions are available at this moment for multimodal-transportation-optimization.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install multimodal-transportation-optimization

You can download it from GitHub.
You can use multimodal-transportation-optimization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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