MOSPP-instances | Multiobjective shortest path problem instances
kandi X-RAY | MOSPP-instances Summary
kandi X-RAY | MOSPP-instances Summary
MOSPP-instances is a C++ library. MOSPP-instances has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
The aim is to produce instances for solving the multiobjective shortest path. We provide realistic data based on the actual street network of some cities. The data comes from OpenStreetMap (for most data and from the STRM project of the NASA for the elevation data. We hope that those instances will allow researcher to test their algorithms and compare their results with other publications. An effort has been made in order to provide easy to use data. The instances are coma separated value files (.csv) that are a natural representation of a graph. Furthermore we provide code samples to import those instances directly in some usual programming languages and libraries. Please note that the instances are based on actual data, but the model has been simplified in order to be easy to manipulate. This data is not meant to be used for real life tools, but for comparing algorithms. A parser has been provided, so that every user can build an instance on the region he disires. A solver implements Martins' algorithm. It is not an state of the art multi-objective shortest path problem solver, but allows to get a exact Pareto front.
The aim is to produce instances for solving the multiobjective shortest path. We provide realistic data based on the actual street network of some cities. The data comes from OpenStreetMap (for most data and from the STRM project of the NASA for the elevation data. We hope that those instances will allow researcher to test their algorithms and compare their results with other publications. An effort has been made in order to provide easy to use data. The instances are coma separated value files (.csv) that are a natural representation of a graph. Furthermore we provide code samples to import those instances directly in some usual programming languages and libraries. Please note that the instances are based on actual data, but the model has been simplified in order to be easy to manipulate. This data is not meant to be used for real life tools, but for comparing algorithms. A parser has been provided, so that every user can build an instance on the region he disires. A solver implements Martins' algorithm. It is not an state of the art multi-objective shortest path problem solver, but allows to get a exact Pareto front.
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MOSPP-instances has a low active ecosystem.
It has 6 star(s) with 1 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
MOSPP-instances has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of MOSPP-instances is current.
Quality
MOSPP-instances has 0 bugs and 0 code smells.
Security
MOSPP-instances has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
MOSPP-instances code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
MOSPP-instances 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.
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MOSPP-instances releases are not available. You will need to build from source code and install.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of MOSPP-instances
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of MOSPP-instances
MOSPP-instances Key Features
No Key Features are available at this moment for MOSPP-instances.
MOSPP-instances Examples and Code Snippets
No Code Snippets are available at this moment for MOSPP-instances.
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Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
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You can download it from GitHub.
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