greedy-tsp | greedily collecting items in open world games

by gajduk Python Version: Current License: MIT

X-Ray Key Features Code Snippets(1)Community Discussions Vulnerabilities Install Support

kandi X-RAY | greedy-tsp Summary

greedy-tsp is a Python library. greedy-tsp has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However greedy-tsp build file is not available. You can download it from GitHub.

#effectiveness of greedily collecting items in open world games. andrej gajduk - andrej at gajduk.com. the traveling salesman problem (tsp) is a well known np-hard problem. it asks the following question: how can a traveling salesman visit all of n cities at least once and return to his starting location in a most efficient manner? efficient in this context can refer to distance, time or money. because of its importance in real world scenarios such as delivery networks and supply chains it has been extensively studied and many optimization algorithms have been proposed in the literature [1,2,3]. however, humans have repeatedly been shown to perform better than computer algorithms on specific instances of the problem [4,5]. another emerging scenario in which tsp is relevant are open world computer games. these games, sometimes also called free roam, allow the player to freely explore a vast virtual world, completing missions and gathering collectibles in his preferred order. some famous games that fall into this category are grand theft auto, world of warcraft, assasins creed and far cry featuring modern urban, fantasy, historic and pacific island settings respectively. most recently, pokemon go used augmented reality to make the whole world a setting for an open world

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Support

greedy-tsp has a low active ecosystem.

It has 4 star(s) with 3 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

greedy-tsp has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of greedy-tsp is current.

Quality

greedy-tsp has no bugs reported.

Security

greedy-tsp has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

greedy-tsp is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

greedy-tsp releases are not available. You will need to build from source code and install.

greedy-tsp has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Greedy greedy algorithm
Compute the distance between two points
Calculate the total distance between two coordinates
Find the optimal distance between start and coords
Calculate the optimal combinations of coordinates

Get all kandi verified functions for this library.

greedy-tsp Key Features

No Key Features are available at this moment for greedy-tsp.

greedy-tsp Examples and Code Snippets

Generate a Greedy TSP .

java

Lines of Code : 97

License : Permissive (MIT License)

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public static void main (String[] args) {
	
	int n = 0;
	long seed = 0;
	DecimalFormat df = new DecimalFormat("0.00");
	
	if (args.length != 2) {
	    System.out.println("Usage: java GreedyTSP n seed");
	    System.exit(0);
	}
	
	try {
	    n = Integ

Community Discussions

No Community Discussions are available at this moment for greedy-tsp.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install greedy-tsp

You can download it from GitHub.
You can use greedy-tsp 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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