Cornelius Croitoru

Learn More
The aim of this paper is to introduce a new evolutionary formulation of the graph coloring problem, based on the interplay between orderings and colorings of vertices. The new formulation breaks symmetry in the solution space and provides opportunities for combining evolutionary and other search tehniques. Our formulation is very simple compared to previous(More)
— Constraint satisfaction arises in many domains in different forms. Search and inference compete for solving constraint satisfaction problems (CSPs) but the most successful approaches are those which benefit from both techniques. Based on this idea, this article introduces a new scheme for solving the general Max-CSP problem. The new approach exploits the(More)
Combining inference and search produces successful schemes for solving constraint satisfaction problems. Based on this idea a general scheme which uses inference inside evolutionary computation techniques is presented. A genetic algorithm and the particle swarm optimization heuristic make use of adaptable inference levels offered by the mini-bucket(More)
In this paper we address the problem of (1)representing bids for combinatorial auctions and (2) employing those structures for Winner Determination. We propose a graph-based language employing generalized network flows to represent the bids. The interpretation of winner determination is then seen as an aggregation of individual preferences. We motivate the(More)
In this paper we introduce a new graph based bidding language for combinatorial auctions. In our language, each bidder submits to the arbitrator a generalized flow network (netbid) representing her bids. The interpretation of the winner determination problem as an aggre-gation of individual preferences represented as flowbids allows building an aggregate(More)