An efficient method to find approximate solutions for combinatorial double auctions

Although combinatorial auctions can be applied to improve the efficiency of trading goods, it is notoriously difficult to solve combinatorial auction problems from a computation point of view. In this paper, we formulate the combinatorial double auction problem and propose an algorithm for finding approximate solutions. The algorithm is developed by decomposing the combinatorial double auction problem into several buyers´ subproblems and sellers´ subproblems, applying the subgradient algorithm to iteratively adjust the shadow prices and proposing a heuristic algorithm for finding approximate solutions. The effectiveness of the proposed algorithm is also illustrated by comparison with an existing solver.