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Distributed path restoration based on optical cross-connects can provide highly capacity-efficient real-time restoration for WDM-based optical networking. However, to obtain an assured restoration level with the theoretically very low amounts of spare capacity that path restoration allows, one must solve, or closely approximate a solution to, the integer multicommodity maximum flow (MCMF) problem, MCMF is, however a hard combinatorial optimization problem due to what is called the "mutual capacity" aspects of the problem: which of many competing origin-destination pairs should be allowed paths over the finite spares on each span? Integer MCMF is further complicated by the nonunimodular nature of the problem, i.e., fractional flows are forbidden but would arise if solved by linear programming. This paper presents a heuristic principle that tests well against integer programming solutions of MCMF routing. The heuristic is first characterized in a centralized program, then adapted for use in a distributed path restoration protocol. In all test cases, the protocol obtains over 97% of the paths found in an optimal MCMF solution in the same network. Via OPNET simulation it is also predicted that the protocol will run in well under 2 seconds which means it could be used directly in real-time, or in distributed prefailure self-planning, for restoration. The significance is that network operators could aggressively optimize their spare capacity, toward theoretical minimums, while still assuring 100% restorability.