An Ant Colony Optimization Algorithm for Partitioning Graphs with Supply
  and Demand
  In this paper we focus on finding high quality solutions for the problem of
maximum partitioning of graphs with supply and demand (MPGSD). There is a
growing interest for the MPGSD due to its close connection to problems
appearing in the field of electrical distribution systems, especially for the
optimization of self-adequacy of interconnected microgrids. We propose an ant
colony optimization algorithm for the problem. With the goal of further
improving the algorithm we combine it with a previously developed correction
procedure. In our computational experiments we evaluate the performance of the
proposed algorithm on both trees and general graphs. The tests show that the
method manages to find optimal solutions in more than 50% of the problem
instances, and has an average relative error of less than 0.5% when compared to
known optimal solutions.
