Combinatorial search problems are usually described by a collection of possible states, a list of possible actions which map each current state into some next state, and a pair of initial and final states. The algorithmic problem is to find a sequence of actions which maps the given initial state into the desired final state. In this paper, we introduce the new notion of bicomposite search problems, and show that they can be solved with improved combinations of time and space complexities by using a new algorithmic paradigm called dissection. To demonstrate the broad applicability of our new paradigm, we show how to use it in order to untangle Rubik's cube and to solve a typical NP-complete partition problem with algorithms which are better than any previously described algorithm for these problems.
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ASJC Scopus subject areas
- Computer Science (all)