| Article ID: | iaor2008750 |
| Country: | Netherlands |
| Volume: | 42 |
| Issue: | 3 |
| Start Page Number: | 1657 |
| End Page Number: | 1672 |
| Publication Date: | Dec 2006 |
| Journal: | Decision Support Systems |
| Authors: | Brydon Michael |
| Keywords: | combinatorial optimization, artificial intelligence: decision support |
The primary advantage of using simulated internal markets to solve complex resource allocation problems is that markets permit much of the computation of a solution to be distributed over a large number of independent agents running on separate processors. The difficulty that arises in the context of NP-hard resource allocation problems is that the market for resources inevitably takes the form of a combinatorial auction; which induces a different type of NP-hard problem. We examine an important class of stochastic, intrafirm resource allocation problems and ask whether economic constructs, such as agents, markets, and prices, provide a useful foundation for structuring decentralized heuristic solution techniques. We show how complex exchange protocols can help market-based search techniques avoid the local maxima problems associated with other greedy search heuristics and converge on good equilibrium solutions.