In recent times combinatorial auctions have become an interesting domain for theoretical and applied developments of the electronic market technology. A combinatorial auction allows the simultaneous selling of several items and each participant to the auction may bid for bundles of items. When items in a bid are all different the auction is said a Single Unit Combinatorial Auction (SUCA), while...

This paper introduces a genetic algorithm enhanced with a trap escaping strategy derived from the dual information presented as discrete Lagrange multipliers. When the genetic algorithm is trapped into a local optima, the Discrete Lagrange Multiplier method is called for the best individual found. The information provided by the Lagrangian method is unified, in the form of recombination, with t...

Although combinatorial auctions have received a great deal of attention from the computer science community over the past decade, research in this domain has focused on settings in which a bidder only has preferences over the bundles of goods they themselves receive, and is indifferent about how other goods are allocated to other bidders. In general, however, bidders in combinatorial auctions w...

Boolean linear programs (BLPs) are ubiquitous in AI. Satisfiability testing, planning with resource constraints, and winner determination in combinatorial auctions are all examples of this type of problem. Although increasingly well-informed by work in OR, current AI research has tended to focus on specialized algorithms for each type of BLP task and has only loosely patterned new algorithms on...

Task allocation is an issue that every multi-robot system must address. Recent task allocation solutions propose an auction based approach wherein robots bid for tasks based on cost functions for performing a task. This paper presents RACHNA, a novel architecture for multi-robot task allocation based on a modified algorithm for the winner determination problem in multi-unit combinatorial auctio...

We prove that for any integer generalized scoring rules (GSRs), winner determination and computing a wide range of strategic behavior are fixed-parameter tractable (FPT) w.r.t. the number of alternatives.

Combinatorial auctions (CAs) are an important mechanism for allocating multiple goods while allowing self-interested agents to specify preferences over bundles of items. Winner determination for a CA is known to be NP-complete. However, restricting the problem can allow us to solve winner determination in polynomial time. These restrictions sometimes apply to the CA’s representation. There are ...

Combinatorial auctions, one of the most popular market mechanisms, have a huge effect on electronic markets and political strategies. Combinatorial auctions provide suitable mechanisms for efficient allocation of resources to self-interested attendees. On the other hand, efficient resource allocation is also becoming crucial in many computer systems that should manage resources efficiently. Con...

Although combinatorial auctions have received a great deal of attention from the computer science community over the past decade, research in this domain has focussed on settings in which a bidder only has preferences over the bundles of goods they themselves receive, and is indifferent about how other goods are allocated to other bidders. In general, however, bidders in combinatorial auctions ...

Mixed Multi-Unit Combinatorial Auctions (MMUCAs) offer a high potential to be employed for the automated assembly of supply chains of agents. However, little is known about the factors making a winner determination problem (WDP) instance hard to solve. In this paper we empirically study the hardness of MMUCAs: (i) to build a model that predicts the time required to solve a WDP instance (because...