DamieDamie / combinatorial_auction

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Combinatorial Auction

Experimenting with algorithm that maximise the profit for Combinatorial Auction problem

Reports

An auxiliary report will be done based on the results of the following experiments:

DataSets

We have the test datasets that can be found here, in total we hage 630 files with auction data.

A special dataset can be found here that is a small subset of the all the datasets that contains some small and large instances, it is mainly used for fast iterations.

Raw data for our experiments can be found here, informations about the experiments can be found in the above reports.

Sources

Every solution is based on this base_model.

We have a few solutions:

  • LP model that can be found here
  • A few greedy implementation that can be found here
    • GreedyBigBet - is ordering bids by the amount they offer
    • GreedyNumberOfItems - is ordering bids by the amount if items the bid contains
    • GreedyAverageItemsPrice - is ordering bids by the average price/item
  • Ant Colony Optimization that can be found here - this is the first solution, we can still improve it
  • Ant Colony Optimization that can be found here that uses 1000 ants to encourage exploration

A utility tool to generate Markdown with tables based on a summary, can be found here.

Also a tool that compared results to one another can be found here, it is already liked to existing experiment results, you can run it and see how differing experiments compare with each other and offer static data on the results.

Team Members:

  • Glodeanu Irina-Elena
  • Micu Matei-Marius

About

License:MIT License


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Language:Python 100.0%