This repository contains the implementation of the algorithm presented by Filippo Bistaffa, Georgios Chalkiadakis, and Alessandro Farinelli in “Efficient Coalition Structure Generation via Approximately Equivalent Induced Subgraph Games”, IEEE Transactions on Cybernetics (IEEE TCYB) volume 52 issue 6, 2021, DOI: 10.1109/TCYB.2020.3040622.
APEQIS requires g++ to compile, and relies on IBM CPLEX to solve the LP model. In order to compile against CPLEX, CPLEXROOT inside Makefile must be set to point to the root folder of CPLEX.
In order to employ Twitter as network topology, java must be installed on the system, and the Twitter GitHub repository must be git clone'd inside APEQIS's root directory.
APEQIS must be executed by means of the apeqis.sh script, i.e.,
./apeqis.sh -t <scalefree|twitter> -n <#agents> -s <seed> [-m <barab_m>] [-d <drivers%>] [-c <out_file>]
-t Network topology (either scalefree or twitter)
-n Number of agents
-s Seed
-d Drivers' percentage (optional, default d = 20)
-m Parameter m of the Barabasi-Albert model (optional, default m = 2)
-c Outputs an input file formatted for CFSS (optional)
APEQIS employs the GeoLife dataset by Microsoft Research presented by Yu Zheng, Quannan Li, Yukun Chen, Xing Xie, and Wei-Ying Ma in “Understanding mobility based on GPS data”, Proceedings of the 10th ACM conference on Ubiquitous Computing (Ubicomp), pages 312−321, 2008, ACM press.