MAX 1 in 2 SAT Algorithm The maximum satisfiability problem (Max-Sat) is the problem of finding the maximum number of clauses that can be satisified in a Boolean satisfiability instance. The exactly 1 in 2 Sat problem asks, given a set of clauses each with two literals, is there a set of literals such that each clause has exactly one literal from this set.

The Complexity of Making Unique Choices: Approximating 1-in-k SAT by Guruswami and Trevisan gives a method for approximating Max 1 in 2 Sat. They state monotone (no negated literals) Max 1 in 2 Sat "admits an e-approximation in polynomial time".

I would like to find an exact algorithm for the Max monotone 1 in 2 Sat problem.
A monotone 1-in-2 clause demands that the two variables have different values. Thus, you can model the problem as a graph problem, with one vertex per variable which is to be colored black or white, and an edge for a clause indicating the colors need to be different. Thus, the question is to make the graph bipartite by deleting a minimum number of edges. This is the MaxCut or Edge Bipartization problem. It is NP-hard.

For Edge Bipartization, there is an algorithm that runs fast when few edges need to be deleted. I wrote an implementation for a slightly more general problem described here (source code).