A Lagrangian approach to the winner determination problem in iterative combinatorial reverse auctions

Abstract

Abstract Combinatorial auctions allow allocation of bundles of items to the bidders who value them the most. The NP -hardness of the winner determination problem (WDP) has imposed serious computational challenges when designing efficient solution algorithms. This paper analytically studies the Lagrangian relaxation of WDP and expounds a novel technique for efficiently solving the relaxation problem. Moreover, we introduce a heuristic algorithm that adjusts any infeasibilities from the Lagrangian optimal solution to reach an optimal or a near optimal solution. Extensive numerical experiments illustrate the class of problems on which application of this technique provides near optimal solutions in much less time, as little as a fraction of a thousand, as compared to the CPLEX solver.