Parallel Search Using Portfolios

Combinatorial search problems can require exponentially growing search cost as the size of the problems increase. Fortunately, a variety of heuristic methods solve many such problems much more rapidly than would be expected from the increasing size of the search space. Such heuristics often have di erent strengths, so running them in parallel can give good performance across a wider range of problems than any individual heuristic. Such approaches, analogous to portfolios in nancial markets, can simultaneously improve expected performance and reduce the performance variation. This paper describes this approach and directions for future work involving cooperative methods and alternate computational devices. Multiple Approaches to Combinatorial