Technical Report: UTEP-CS-13-19

To appear in Journal of Uncertain Systems, 2013, Vol. 7.


Many real-life problems are, in general, NP-hard, i.e., informally speaking, are difficult to solve. To be more precise, a problem p is NP-hard means that every problem from the class NP can be reduced to this problem p. Thus, if we have an efficient algorithm for solving one NP-hard problem, we can use this reduction to get a more efficient way of solving all the problems from the class NP. To speed up computations, it is reasonable to base them on the fastest possible physical process -- i.e., on light. It is known that analog optical processing indeed speeds up computation of several NP-hard problems. Each of the corresponding speed-up schemes has its success cases and limitations. The more schemes we know, the higher the possibility that for a given problem, one of these schemes will prove to be effective. Motivated by this argument, we propose a new analog optical processing scheme for solving NP-hard problems.